{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import torch\n",
    "from torch.utils.data import Dataset\n",
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "df = pd.read_csv(\"./datas/salarys.csv\",encoding='utf8')\n",
    "def z_score(series):\n",
    "    #计算均值\n",
    "    _mean = series.sum()/series.count()\n",
    "    print(\"mean:{}\".format(_mean))\n",
    "    #计算标准差\n",
    "    std = (((series-_mean)**2).sum()/(series.count()-1))**0.5\n",
    "    print(\"std:{}\".format(std))\n",
    "    new_series = (series-_mean)/std\n",
    "    return new_series\n",
    "def transform(data):\n",
    "        return data\n",
    "class CustomDataset(Dataset):\n",
    "    def __init__(self, csv_path, transform=transform):\n",
    "        self.transform = transform  #数据预处理方法\n",
    "        df = pd.read_csv(csv_path, encoding='utf8') #读取数据\n",
    "        #纬度有nan值，采用前向填充\n",
    "        df = df.fillna(method=\"ffill\")\n",
    "        del df['专业']\n",
    "        del df['省份']\n",
    "        del df['城市']\n",
    "        #需要进行One-Hot编码的字段\n",
    "        self.zy =sorted(set(df[\"专业编码\"].values))\n",
    "        self.wd = sorted(set(df[\"纬度\"].values))\n",
    "        self.jd = sorted(set(df[\"经度\"].values))\n",
    "        self.sf = sorted(set(df[\"省份编码\"].values))\n",
    "        self.xl = sorted(set(df[\"学历编码\"].values))\n",
    "        \n",
    "        \n",
    "        self.df_label = df[\"薪酬\"]\n",
    "        del df[\"薪酬\"]\n",
    "        #对“综合能力”归一化处理\n",
    "        df[\"综合能力\"] = z_score(df[\"综合能力\"])\n",
    "        self.df_data = df \n",
    "        self.columns = self.df_data.columns.tolist()\n",
    "\n",
    "    def __getitem__(self, idx):  # 根据 idx 取出其中一个\n",
    "        data = self.df_data.iloc[idx].values\n",
    "        label = self.df_label.iloc[idx]\n",
    "        return data,torch.tensor(label)\n",
    "    \n",
    "    def __len__(self):  # 总数据的多少\n",
    "        return df.count()[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "mean:37.07904970227501\n",
      "std:21.75875929994074\n"
     ]
    }
   ],
   "source": [
    "dataset = CustomDataset(\"./datas/salarys.csv\",transform=transform)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[ 2.00000000e+00  1.70300000e+03  0.00000000e+00  0.00000000e+00\n",
      "  4.10000000e+01  1.23000000e+02  1.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  2.40000000e+01 -7.06774568e-01] tensor(5531.9990)\n",
      "[ 11.         517.           0.           0.          31.\n",
      " 121.           0.           2.           0.           0.\n",
      "   0.           0.           0.          33.           1.95167241] tensor(20783.7949)\n",
      "[  2.          57.           0.           1.          31.\n",
      " 121.           0.           2.           3.           0.\n",
      "   0.           0.           0.          31.          -0.51104337] tensor(5902.6431)\n",
      "[ 2.          9.          0.          1.         42.         86.\n",
      "  0.          0.          0.          0.          0.          0.\n",
      "  0.         27.          1.11436842] tensor(9718.1426)\n",
      "[  2.         297.           0.           1.          45.\n",
      " 126.           1.           0.           0.           0.\n",
      "   0.           0.           0.          15.           1.42012124] tensor(11063.9980)\n",
      "[ 1.00000000e+00  8.73000000e+02  0.00000000e+00  0.00000000e+00\n",
      "  4.20000000e+01  8.60000000e+01  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  3.10000000e+01 -7.06774568e-01] tensor(5531.9990)\n",
      "[  1.         156.           0.           0.          38.\n",
      " 115.           0.           2.           0.           0.\n",
      "   0.           0.           0.          33.           0.93187116] tensor(9107.9121)\n",
      "[ 1.00000000e+00  4.07000000e+02  1.00000000e+00  1.00000000e+00\n",
      "  3.50000000e+01  1.16000000e+02  0.00000000e+00  2.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  3.10000000e+01 -3.01143857e-01] tensor(6298.1201)\n",
      "[ 2.00000000e+00  6.49000000e+02  0.00000000e+00  1.00000000e+00\n",
      "  3.20000000e+01  1.09000000e+02  0.00000000e+00  2.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  3.30000000e+01 -3.01143857e-01] tensor(6298.1201)\n",
      "[  1.         769.           0.           0.          45.\n",
      " 126.           0.           2.           3.           3.\n",
      "   0.           0.           0.          33.          -1.29818526] tensor(4268.)\n",
      "[1.0000000e+00 8.5200000e+02 0.0000000e+00 1.0000000e+00 3.0000000e+01\n",
      " 1.1400000e+02 0.0000000e+00 2.0000000e+00 0.0000000e+00 0.0000000e+00\n",
      " 0.0000000e+00 0.0000000e+00 0.0000000e+00 3.3000000e+01 5.1998844e-01] tensor(8000.)\n",
      "[2.00000000e+00 1.70300000e+03 0.00000000e+00 0.00000000e+00\n",
      " 4.20000000e+01 8.60000000e+01 0.00000000e+00 0.00000000e+00\n",
      " 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00\n",
      " 0.00000000e+00 3.10000000e+01 3.68223674e-01] tensor(7650.7529)\n",
      "[ 1.00000000e+00  6.55000000e+02  0.00000000e+00  1.00000000e+00\n",
      "  3.10000000e+01  1.21000000e+02  0.00000000e+00  2.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  3.10000000e+01 -2.46441106e-01] tensor(6402.)\n",
      "[  2.         297.           0.           1.          34.\n",
      " 119.           1.           0.           0.           0.\n",
      "   0.           0.           0.          16.          -0.70677457] tensor(5531.9990)\n",
      "[ 2.00000000e+00  1.70300000e+03  0.00000000e+00  0.00000000e+00\n",
      "  3.20000000e+01  1.17000000e+02  1.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  2.90000000e+01 -1.04358761e+00] tensor(4859.0713)\n",
      "[ 2.00000000e+00  3.10000000e+02  0.00000000e+00  1.00000000e+00\n",
      "  3.10000000e+01  1.21000000e+02  0.00000000e+00  2.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  2.90000000e+01 -2.46441106e-01] tensor(6402.)\n",
      "[  2.         257.           1.           1.          30.\n",
      " 114.           1.           0.           0.           0.\n",
      "   0.           0.           0.          25.          -1.39501774] tensor(4000.)\n",
      "[1.00000000e+00 1.70300000e+03 0.00000000e+00 0.00000000e+00\n",
      " 3.00000000e+01 1.20000000e+02 0.00000000e+00 2.00000000e+00\n",
      " 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00\n",
      " 0.00000000e+00 3.30000000e+01 4.24233531e-01] tensor(7776.9434)\n",
      "[  1.         160.           1.           1.          32.\n",
      " 119.           1.           0.           0.           0.\n",
      "   0.           0.           0.          16.          -1.04358761] tensor(4859.0713)\n",
      "[  2.         851.           0.           1.          23.\n",
      " 113.           1.           0.           0.           0.\n",
      "   0.           0.           0.          30.          -1.29818526] tensor(4268.)\n",
      "[ 1.00000000e+00  8.40000000e+02  0.00000000e+00  1.00000000e+00\n",
      "  3.00000000e+01  1.14000000e+02  0.00000000e+00  2.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  3.00000000e+01 -4.59278471e-01] tensor(6000.)\n",
      "[  1.         311.           0.           1.          32.\n",
      " 118.           0.           2.           3.           3.\n",
      "   0.           0.           0.          26.          -0.88503262] tensor(5184.6289)\n",
      "[ 2.00000000e+00  1.70300000e+03  0.00000000e+00  0.00000000e+00\n",
      "  3.10000000e+01  1.04000000e+02  1.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  2.70000000e+01 -1.18132525e+00] tensor(4553.9561)\n",
      "[  1.         734.           1.           1.          42.\n",
      "  86.           0.           0.           0.           0.\n",
      "   0.           0.           0.          27.          -1.29818526] tensor(4268.)\n",
      "[  2.         407.           1.           1.          30.\n",
      " 112.           1.           0.           0.           0.\n",
      "   0.           0.           0.          29.           1.82760652] tensor(15000.)\n",
      "[  1.         407.           1.           1.          39.\n",
      " 116.           0.           2.           0.           0.\n",
      "   0.           0.           0.          31.          -1.18132525] tensor(4553.9561)\n",
      "[  2.         160.           1.           1.          34.\n",
      " 108.           0.           2.           0.           0.\n",
      "   0.           0.           0.          33.          -0.70677457] tensor(5531.9990)\n",
      "[  1.         554.           1.           1.          29.\n",
      " 121.           0.           2.           3.           0.\n",
      "   0.           0.           0.          33.           1.86966682] tensor(16005.)\n",
      "[  2.         257.           1.           1.          42.\n",
      "  86.           0.           0.           0.           0.\n",
      "   0.           0.           0.          29.          -0.70677457] tensor(5531.9990)\n",
      "[  2.         160.           1.           1.          42.\n",
      "  86.           0.           0.           0.           0.\n",
      "   0.           0.           0.          30.           1.34300582] tensor(10670.)\n",
      "[  1.        749.          0.          1.         29.        106.\n",
      "   0.          2.          0.          0.          0.          0.\n",
      "   0.         33.          1.2775747] tensor(10369.2578)\n",
      "[  1.         629.           0.           1.          32.\n",
      " 109.           0.           2.           0.           0.\n",
      "   0.           0.           0.          33.          -1.04358761] tensor(4859.0713)\n",
      "[  1.         465.           0.           1.          41.\n",
      " 123.           0.           2.           0.           0.\n",
      "   0.           0.           0.          33.           1.11436842] tensor(9718.1426)\n",
      "[1.00000000e+00 1.70300000e+03 0.00000000e+00 0.00000000e+00\n",
      " 3.60000000e+01 1.14000000e+02 0.00000000e+00 2.00000000e+00\n",
      " 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00\n",
      " 0.00000000e+00 3.10000000e+01 7.32566829e-01] tensor(8536.)\n",
      "[ 2.00000000e+00  1.70300000e+03  0.00000000e+00  0.00000000e+00\n",
      "  4.20000000e+01  1.23000000e+02  1.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  2.60000000e+01 -1.04358761e+00] tensor(4859.0713)\n",
      "[2.00000000e+00 1.70300000e+03 0.00000000e+00 0.00000000e+00\n",
      " 4.20000000e+01 8.60000000e+01 0.00000000e+00 0.00000000e+00\n",
      " 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00\n",
      " 0.00000000e+00 3.30000000e+01 2.00470543e-01] tensor(7288.6064)\n",
      "[   2.         1703.            0.            0.           42.\n",
      "   86.            0.            0.            0.            0.\n",
      "    0.            0.            0.           26.            1.96709287] tensor(25000.)\n",
      "[  1.         649.           0.           1.          27.\n",
      " 110.           0.           2.           0.           0.\n",
      "   0.           0.           0.          30.           0.93187116] tensor(9107.9121)\n",
      "[  2.         257.           1.           1.          42.\n",
      "  86.           0.           0.           0.           0.\n",
      "   0.           0.           0.          23.           0.84684595] tensor(8853.9639)\n",
      "[  1.         837.           0.           1.          28.\n",
      " 115.           0.           2.           0.           0.\n",
      "   0.           0.           0.          30.          -1.04358761] tensor(4859.0713)\n",
      "[  1.         652.           0.           1.          34.\n",
      " 108.           0.           2.           0.           0.\n",
      "   0.           0.           0.          31.          -1.18132525] tensor(4553.9561)\n",
      "[1.20000000e+01 8.42000000e+02 0.00000000e+00 1.00000000e+00\n",
      " 4.20000000e+01 8.60000000e+01 0.00000000e+00 0.00000000e+00\n",
      " 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00\n",
      " 0.00000000e+00 3.00000000e+01 2.00470543e-01] tensor(7288.6064)\n",
      "[ 2.00000000e+00  1.70300000e+03  0.00000000e+00  0.00000000e+00\n",
      "  3.20000000e+01  1.05000000e+02  1.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  2.80000000e+01 -2.46441106e-01] tensor(6402.)\n",
      "[  2.         554.           1.           1.          30.\n",
      " 114.           0.           2.           0.           0.\n",
      "   0.           0.           0.          33.           1.54171779] tensor(11805.2861)\n",
      "[ 1.00000000e+00  1.70300000e+03  0.00000000e+00  0.00000000e+00\n",
      "  4.30000000e+01  1.25000000e+02  0.00000000e+00  2.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  3.30000000e+01 -1.29818526e+00] tensor(4268.)\n",
      "[1.00000000e+00 8.51000000e+02 0.00000000e+00 1.00000000e+00\n",
      " 3.00000000e+01 1.14000000e+02 0.00000000e+00 2.00000000e+00\n",
      " 3.00000000e+00 3.00000000e+00 0.00000000e+00 0.00000000e+00\n",
      " 0.00000000e+00 3.00000000e+01 4.24233531e-01] tensor(7776.9434)\n",
      "[  2.         310.           0.           1.          37.\n",
      " 112.           1.           0.           0.           0.\n",
      "   0.           0.           0.          16.          -0.70677457] tensor(5531.9990)\n",
      "[1.00000000e+00 7.36000000e+02 0.00000000e+00 1.00000000e+00\n",
      " 2.80000000e+01 1.12000000e+02 0.00000000e+00 2.00000000e+00\n",
      " 3.00000000e+00 3.00000000e+00 0.00000000e+00 0.00000000e+00\n",
      " 3.00000000e+00 3.30000000e+01 6.41262404e-01] tensor(8297.9980)\n",
      "[  1.         230.           0.           1.          24.\n",
      " 117.           0.           2.           0.           0.\n",
      "   0.           0.           0.          33.          -1.29818526] tensor(4268.)\n",
      "[  1.           9.           0.           1.          34.\n",
      " 108.           0.           2.           3.           3.\n",
      "   0.           0.           0.          33.          -0.30114386] tensor(6298.1201)\n",
      "[  3.           9.           0.           1.          31.\n",
      " 121.           0.           2.           0.           0.\n",
      "   0.           0.           0.          31.           0.20047054] tensor(7288.6064)\n",
      "[ 2.00000000e+00  1.70300000e+03  0.00000000e+00  0.00000000e+00\n",
      "  3.10000000e+01  1.04000000e+02  1.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  3.30000000e+01 -1.29818526e+00] tensor(4268.)\n",
      "[ 2.00000000e+00  1.70300000e+03  0.00000000e+00  0.00000000e+00\n",
      "  2.80000000e+01  1.13000000e+02  1.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  3.00000000e+01 -5.11043371e-01] tensor(5902.6431)\n",
      "[  1.         722.           0.           0.          43.\n",
      " 125.           0.           2.           3.           3.\n",
      "   0.           0.           0.          33.          -0.88503262] tensor(5184.6289)\n",
      "[ 1.00000000e+00  8.51000000e+02  0.00000000e+00  1.00000000e+00\n",
      "  2.60000000e+01  1.01000000e+02  0.00000000e+00  2.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  3.30000000e+01 -3.01143857e-01] tensor(6298.1201)\n",
      "[  1.         257.           1.           1.          32.\n",
      " 118.           0.           2.           3.           0.\n",
      "   0.           0.           0.          33.          -1.18132525] tensor(4553.9561)\n",
      "[  1.         407.           1.           1.          42.\n",
      "  86.           0.           0.           0.           0.\n",
      "   0.           0.           0.          33.           1.42012124] tensor(11063.9980)\n",
      "[ 4.00000000e+00  1.70300000e+03  0.00000000e+00  0.00000000e+00\n",
      "  4.20000000e+01  8.60000000e+01  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  1.40000000e+01 -8.85032618e-01] tensor(5184.6289)\n",
      "[  1.         159.           1.           1.          34.\n",
      " 108.           0.           2.           3.           3.\n",
      "   0.           0.           0.          28.           0.84684595] tensor(8853.9639)\n",
      "[  2.         160.           1.           1.          23.\n",
      " 114.           1.           0.           0.           0.\n",
      "   0.           0.           0.          31.          -0.70677457] tensor(5531.9990)\n",
      "[  2.         734.           1.           1.          25.\n",
      " 113.           1.           0.           0.           0.\n",
      "   0.           0.           0.          30.          -0.88503262] tensor(5184.6289)\n",
      "[1.00000000e+00 1.70300000e+03 0.00000000e+00 0.00000000e+00\n",
      " 4.20000000e+01 8.60000000e+01 0.00000000e+00 0.00000000e+00\n",
      " 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00\n",
      " 0.00000000e+00 3.10000000e+01 2.00470543e-01] tensor(7288.6064)\n",
      "[1.0000000e+00 1.7030000e+03 0.0000000e+00 0.0000000e+00 4.2000000e+01\n",
      " 8.6000000e+01 0.0000000e+00 0.0000000e+00 0.0000000e+00 0.0000000e+00\n",
      " 0.0000000e+00 0.0000000e+00 0.0000000e+00 3.3000000e+01 5.1998844e-01] tensor(8000.)\n",
      "[  2.         410.           0.           1.          42.\n",
      "  86.           0.           0.           0.           0.\n",
      "   0.           0.           0.          33.          -1.18132525] tensor(4553.9561)\n",
      "[ 11.         873.           0.           0.          42.\n",
      "  86.           0.           0.           0.           0.\n",
      "   0.           0.           0.          31.           1.42012124] tensor(11063.9980)\n",
      "[  1.         753.           0.           1.          23.\n",
      " 113.           0.           2.           0.           0.\n",
      "   0.           0.           0.          30.          -1.29818526] tensor(4268.)\n",
      "[  1.         652.           0.           1.          34.\n",
      " 109.           0.           2.           0.           0.\n",
      "   0.           0.           0.          33.          -1.18132525] tensor(4553.9561)\n",
      "[  1.         629.           0.           1.          30.\n",
      " 114.           0.           2.           0.           0.\n",
      "   0.           0.           0.          25.          -1.04358761] tensor(4859.0713)\n",
      "[  1.         649.           0.           1.          28.\n",
      " 112.           0.           2.           3.           3.\n",
      "   0.           0.           0.          30.           1.34300582] tensor(10670.)\n",
      "[ 2.00000000e+00  1.70300000e+03  0.00000000e+00  0.00000000e+00\n",
      "  4.20000000e+01  8.60000000e+01  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  2.30000000e+01 -1.29818526e+00] tensor(4268.)\n",
      "[ 2.00000000e+00  9.44000000e+02  0.00000000e+00  1.00000000e+00\n",
      "  2.90000000e+01  1.06000000e+02  1.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  3.30000000e+01 -7.06774568e-01] tensor(5531.9990)\n",
      "[2.00000000e+00 7.34000000e+02 1.00000000e+00 1.00000000e+00\n",
      " 3.40000000e+01 1.08000000e+02 0.00000000e+00 2.00000000e+00\n",
      " 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00\n",
      " 0.00000000e+00 3.00000000e+01 6.41262404e-01] tensor(8297.9980)\n",
      "[ 1.00000000e+00  2.57000000e+02  1.00000000e+00  1.00000000e+00\n",
      "  3.40000000e+01  1.08000000e+02  0.00000000e+00  2.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  3.30000000e+01 -2.48496109e-02] tensor(6830.9341)\n",
      "[  1.         869.           0.           1.          39.\n",
      " 121.           0.           2.           0.           0.\n",
      "   0.           0.           0.          33.          -1.04358761] tensor(4859.0713)\n",
      "[  1.          10.           0.           1.          32.\n",
      " 118.           0.           2.           0.           0.\n",
      "   0.           0.           0.          29.          -0.88503262] tensor(5184.6289)\n",
      "[  1.         841.           0.           1.          29.\n",
      " 121.           0.           2.           0.           0.\n",
      "   0.           0.           0.          33.          -1.29818526] tensor(4268.)\n",
      "[ 2.00000000e+00  8.51000000e+02  0.00000000e+00  1.00000000e+00\n",
      "  2.30000000e+01  1.13000000e+02  1.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  3.00000000e+01 -2.48496109e-02] tensor(6830.9341)\n",
      "[1.00000000e+00 6.52000000e+02 0.00000000e+00 1.00000000e+00\n",
      " 4.20000000e+01 8.60000000e+01 0.00000000e+00 0.00000000e+00\n",
      " 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00\n",
      " 0.00000000e+00 3.30000000e+01 3.68223674e-01] tensor(7650.7529)\n",
      "[ 1.          9.          0.          1.         42.         86.\n",
      "  0.          0.          0.          0.          0.          0.\n",
      "  0.         29.         -1.04358761] tensor(4859.0713)\n",
      "[ 1.00000000e+00  7.64000000e+02  0.00000000e+00  1.00000000e+00\n",
      "  2.70000000e+01  1.02000000e+02  0.00000000e+00  2.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  3.30000000e+01 -3.01143857e-01] tensor(6298.1201)\n",
      "[ 2.00000000e+00  8.40000000e+02  0.00000000e+00  1.00000000e+00\n",
      "  3.10000000e+01  1.20000000e+02  1.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  2.90000000e+01 -2.48496109e-02] tensor(6830.9341)\n",
      "[1.00000000e+00 7.54000000e+02 0.00000000e+00 1.00000000e+00\n",
      " 2.30000000e+01 1.13000000e+02 0.00000000e+00 2.00000000e+00\n",
      " 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00\n",
      " 0.00000000e+00 3.10000000e+01 3.68223674e-01] tensor(7650.7529)\n",
      "[  1.        257.          1.          1.         34.        108.\n",
      "   0.          2.          0.          0.          0.          0.\n",
      "   0.         33.          0.6412624] tensor(8297.9980)\n",
      "[ 3.00000000e+00  1.70300000e+03  0.00000000e+00  0.00000000e+00\n",
      "  4.20000000e+01  8.60000000e+01  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  3.00000000e+01 -1.53347923e+00] tensor(3521.1001)\n",
      "[  1.         840.           0.           1.          42.\n",
      "  86.           0.           0.           0.           0.\n",
      "   0.           0.           0.          30.           1.64302154] tensor(12596.2402)\n",
      "[  1.        9.        0.        1.       30.      120.        0.\n",
      "   2.        0.        0.        0.        0.        0.       33.\n",
      "   0.58742] tensor(8163.3535)\n",
      "[  1.         944.           0.           1.          37.\n",
      " 117.           0.           2.           0.           0.\n",
      "   0.           0.           0.          31.           1.68158211] tensor(12961.5723)\n",
      "[  1.         289.           0.           1.          26.\n",
      " 106.           0.           2.           0.           0.\n",
      "   0.           0.           0.          33.          -0.88503262] tensor(5184.6289)\n",
      "[  1.           9.           0.           1.          39.\n",
      " 116.           0.           2.           0.           0.\n",
      "   0.           0.           0.          23.           0.42423353] tensor(7776.9434)\n",
      "[ 1.00000000e+00  7.53000000e+02  0.00000000e+00  1.00000000e+00\n",
      "  3.10000000e+01  1.18000000e+02  0.00000000e+00  2.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  3.30000000e+01 -2.48496109e-02] tensor(6830.9341)\n",
      "[  2.         150.           0.           0.          42.\n",
      "  86.           0.           0.           0.           0.\n",
      "   0.           0.           0.          26.           1.75628398] tensor(13829.9971)\n",
      "[  1.         840.           0.           1.          37.\n",
      " 121.           0.           2.           0.           0.\n",
      "   0.           0.           0.          31.          -1.29818526] tensor(4268.)\n",
      "[ 1.00000000e+00  9.44000000e+02  0.00000000e+00  1.00000000e+00\n",
      "  3.00000000e+01  1.14000000e+02  0.00000000e+00  2.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  3.30000000e+01 -3.01143857e-01] tensor(6298.1201)\n",
      "[  1.         635.           0.           1.          34.\n",
      " 108.           0.           2.           0.           0.\n",
      "   0.           0.           0.          28.           0.93187116] tensor(9107.9121)\n",
      "[  1.         735.           0.           1.          37.\n",
      " 114.           0.           2.           0.           0.\n",
      "   0.           0.           0.          31.           1.42012124] tensor(11063.9980)\n",
      "[  1.         734.           1.           1.          42.\n",
      "  86.           0.           0.           0.           0.\n",
      "   0.           0.           0.          25.           1.96413774] tensor(23617.9492)\n",
      "[ 1.00000000e+00  7.34000000e+02  1.00000000e+00  1.00000000e+00\n",
      "  3.60000000e+01  1.17000000e+02  0.00000000e+00  2.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  3.30000000e+01 -2.48496109e-02] tensor(6830.9341)\n",
      "[  1.         159.           1.           1.          45.\n",
      " 126.           0.           2.           0.           0.\n",
      "   0.           0.           0.          33.          -1.29818526] tensor(4268.)\n",
      "[ 1.00000000e+00  4.07000000e+02  1.00000000e+00  1.00000000e+00\n",
      "  3.80000000e+01  1.21000000e+02  0.00000000e+00  2.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  3.30000000e+01 -3.01143857e-01] tensor(6298.1201)\n",
      "[2.00000000e+00 1.70300000e+03 0.00000000e+00 0.00000000e+00\n",
      " 3.80000000e+01 1.14000000e+02 0.00000000e+00 2.00000000e+00\n",
      " 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00\n",
      " 0.00000000e+00 3.30000000e+01 7.32566829e-01] tensor(8536.)\n",
      "[  2.         870.           0.           1.          45.\n",
      " 126.           1.           0.           0.           0.\n",
      "   0.           0.           0.          33.          -1.04358761] tensor(4859.0713)\n",
      "[1.00000000e+00 4.07000000e+02 1.00000000e+00 1.00000000e+00\n",
      " 3.90000000e+01 1.16000000e+02 0.00000000e+00 2.00000000e+00\n",
      " 3.00000000e+00 3.00000000e+00 0.00000000e+00 0.00000000e+00\n",
      " 0.00000000e+00 3.10000000e+01 3.68223674e-01] tensor(7650.7529)\n",
      "[  2.         160.           1.           1.          29.\n",
      " 106.           0.           2.           0.           0.\n",
      "   0.           0.           0.          33.           0.84684595] tensor(8853.9639)\n",
      "[  1.         160.           1.           1.          49.\n",
      " 119.           0.           2.           0.           0.\n",
      "   0.           0.           0.           9.          -1.29818526] tensor(4268.)\n",
      "[ 1.00000000e+00  6.49000000e+02  0.00000000e+00  1.00000000e+00\n",
      "  3.40000000e+01  1.13000000e+02  0.00000000e+00  2.00000000e+00\n",
      "  3.00000000e+00  3.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  3.30000000e+01 -4.59278471e-01] tensor(6000.)\n",
      "[  1.         649.           0.           1.          26.\n",
      " 106.           0.           2.           0.           0.\n",
      "   0.           0.           0.          33.          -1.39501774] tensor(4000.)\n",
      "[  1.         852.           0.           1.          30.\n",
      " 103.           0.           2.           0.           0.\n",
      "   0.           0.           0.          27.          -1.39501774] tensor(4000.)\n",
      "[ 2.00000000e+00  1.70300000e+03  0.00000000e+00  0.00000000e+00\n",
      "  3.50000000e+01  1.13000000e+02  0.00000000e+00  2.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  3.10000000e+01 -2.46441106e-01] tensor(6402.)\n",
      "[ 1.00000000e+00  7.72000000e+02  0.00000000e+00  1.00000000e+00\n",
      "  4.20000000e+01  8.60000000e+01  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  3.30000000e+01 -5.11043371e-01] tensor(5902.6431)\n",
      "[  1.         489.           0.           1.          36.\n",
      " 114.           0.           2.           0.           0.\n",
      "   0.           0.           0.          29.           1.34300582] tensor(10670.)\n",
      "[2.0000000e+00 5.5400000e+02 1.0000000e+00 1.0000000e+00 3.4000000e+01\n",
      " 1.1400000e+02 1.0000000e+00 0.0000000e+00 0.0000000e+00 0.0000000e+00\n",
      " 0.0000000e+00 0.0000000e+00 0.0000000e+00 3.3000000e+01 5.1998844e-01] tensor(8000.)\n",
      "[2.00000000e+00 1.70300000e+03 0.00000000e+00 0.00000000e+00\n",
      " 4.20000000e+01 8.60000000e+01 0.00000000e+00 0.00000000e+00\n",
      " 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00\n",
      " 0.00000000e+00 2.90000000e+01 1.58881165e+00] tensor(12147.6777)\n",
      "[  1.         944.           0.           1.          42.\n",
      "  86.           0.           0.           0.           0.\n",
      "   0.           0.           0.          33.           1.92387304] tensor(18221.5156)\n",
      "[1.00000000e+00 8.42000000e+02 0.00000000e+00 1.00000000e+00\n",
      " 4.20000000e+01 8.60000000e+01 0.00000000e+00 0.00000000e+00\n",
      " 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00\n",
      " 0.00000000e+00 2.50000000e+01 7.32566829e-01] tensor(8536.)\n",
      "[  2.         634.           0.           1.          30.\n",
      " 114.           1.           0.           0.           0.\n",
      "   0.           0.           0.          31.          -0.88503262] tensor(5184.6289)\n",
      "[  1.         747.           0.           1.          31.\n",
      " 121.           0.           2.           3.           3.\n",
      "   4.           0.           3.          33.           1.82760652] tensor(15000.)\n",
      "[  1.         151.           0.           1.          36.\n",
      " 116.           0.           2.           0.           0.\n",
      "   0.           0.           0.          33.           0.36822367] tensor(7650.7529)\n",
      "[  1.         836.           0.           1.          45.\n",
      " 126.           0.           2.           0.           0.\n",
      "   0.           0.           0.          33.          -0.88503262] tensor(5184.6289)\n",
      "[ 1.00000000e+00  7.18000000e+02  0.00000000e+00  1.00000000e+00\n",
      "  3.10000000e+01  1.18000000e+02  0.00000000e+00  2.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  3.10000000e+01 -7.06774568e-01] tensor(5531.9990)\n",
      "[  2.         851.           0.           1.          34.\n",
      " 114.           1.           0.           0.           0.\n",
      "   0.           0.           0.          31.          -1.04358761] tensor(4859.0713)\n",
      "[  1.         635.           0.           1.          45.\n",
      " 126.           0.           2.           3.           3.\n",
      "   0.           0.           0.          31.           1.95906438] tensor(22134.9102)\n",
      "[  1.         257.           1.           1.          41.\n",
      " 123.           0.           2.           0.           0.\n",
      "   0.           0.           0.          31.          -0.88503262] tensor(5184.6289)\n",
      "[1.00000000e+00 6.52000000e+02 0.00000000e+00 1.00000000e+00\n",
      " 2.60000000e+01 1.01000000e+02 0.00000000e+00 2.00000000e+00\n",
      " 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00\n",
      " 0.00000000e+00 2.80000000e+01 6.41262404e-01] tensor(8297.9980)\n",
      "[ 1.00000000e+00  5.43000000e+02  0.00000000e+00  1.00000000e+00\n",
      "  3.20000000e+01  1.18000000e+02  0.00000000e+00  2.00000000e+00\n",
      "  3.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  3.30000000e+01 -2.46441106e-01] tensor(6402.)\n",
      "[  1.         554.           1.           1.          28.\n",
      " 115.           0.           2.           0.           0.\n",
      "   0.           0.           0.          14.           1.34300582] tensor(10670.)\n",
      "[  1.         311.           0.           1.          29.\n",
      " 106.           0.           2.           0.           0.\n",
      "   0.           0.           0.          33.           1.75628398] tensor(13829.9971)\n",
      "[ 1.00000000e+00  9.00000000e+00  0.00000000e+00  1.00000000e+00\n",
      "  3.10000000e+01  1.04000000e+02  0.00000000e+00  2.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  3.30000000e+01 -2.48496109e-02] tensor(6830.9341)\n",
      "[  1.         842.           0.           1.          42.\n",
      "  86.           0.           0.           0.           0.\n",
      "   0.           0.           0.          33.          -1.04358761] tensor(4859.0713)\n",
      "[  1.         407.           1.           1.          30.\n",
      " 103.           0.           2.           0.           0.\n",
      "   0.           0.           0.          30.          -1.18132525] tensor(4553.9561)\n",
      "[ 2.00000000e+00  8.51000000e+02  0.00000000e+00  1.00000000e+00\n",
      "  3.10000000e+01  1.20000000e+02  1.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  2.60000000e+01 -4.59278471e-01] tensor(6000.)\n",
      "[ 2.00000000e+00  1.70300000e+03  0.00000000e+00  0.00000000e+00\n",
      "  3.60000000e+01  1.17000000e+02  1.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  2.30000000e+01 -7.06774568e-01] tensor(5531.9990)\n",
      "[  1.         363.           0.           1.          23.\n",
      " 113.           0.           2.           3.           3.\n",
      "   0.           0.           0.          30.           1.58881165] tensor(12147.6777)\n",
      "[2.00000000e+00 6.35000000e+02 0.00000000e+00 1.00000000e+00\n",
      " 3.00000000e+01 1.14000000e+02 0.00000000e+00 2.00000000e+00\n",
      " 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00\n",
      " 0.00000000e+00 3.00000000e+01 4.24233531e-01] tensor(7776.9434)\n",
      "[2.00000000e+00 5.54000000e+02 1.00000000e+00 1.00000000e+00\n",
      " 4.10000000e+01 1.23000000e+02 0.00000000e+00 2.00000000e+00\n",
      " 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00\n",
      " 0.00000000e+00 3.30000000e+01 4.24233531e-01] tensor(7776.9434)\n",
      "[ 1.00000000e+00  7.53000000e+02  0.00000000e+00  1.00000000e+00\n",
      "  2.80000000e+01  1.16000000e+02  0.00000000e+00  2.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  1.40000000e+01 -7.06774568e-01] tensor(5531.9990)\n",
      "[  2.         635.           0.           1.          30.\n",
      " 120.           1.           0.           0.           0.\n",
      "   0.           0.           0.          28.          -0.70677457] tensor(5531.9990)\n",
      "[ 1.00000000e+00  1.59000000e+02  1.00000000e+00  1.00000000e+00\n",
      "  4.20000000e+01  8.60000000e+01  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  3.30000000e+01 -2.48496109e-02] tensor(6830.9341)\n",
      "[  2.          80.           0.           1.          22.\n",
      " 108.           0.           2.           0.           0.\n",
      "   0.           0.           0.          12.          -0.51104337] tensor(5902.6431)\n",
      "[2.00000000e+00 1.70300000e+03 0.00000000e+00 0.00000000e+00\n",
      " 3.00000000e+01 1.12000000e+02 0.00000000e+00 2.00000000e+00\n",
      " 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00\n",
      " 0.00000000e+00 3.30000000e+01 4.24233531e-01] tensor(7776.9434)\n",
      "[  1.         842.           0.           1.          23.\n",
      " 113.           0.           2.           0.           0.\n",
      "   0.           0.           0.          30.          -1.18132525] tensor(4553.9561)\n",
      "[  1.         348.           0.           1.          30.\n",
      " 114.           0.           2.           3.           3.\n",
      "   0.           0.           0.          31.           0.73256683] tensor(8536.)\n",
      "[1.00000000e+00 8.52000000e+02 0.00000000e+00 1.00000000e+00\n",
      " 3.00000000e+01 1.14000000e+02 0.00000000e+00 2.00000000e+00\n",
      " 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00\n",
      " 0.00000000e+00 3.00000000e+01 1.43569229e-01] tensor(7170.3403)\n",
      "[  2.         160.           1.           1.          39.\n",
      " 116.           1.           0.           0.           0.\n",
      "   0.           0.           0.          31.          -0.70677457] tensor(5531.9990)\n",
      "[  1.        266.          0.          1.         39.        117.\n",
      "   0.          2.          3.          0.          0.          0.\n",
      "   0.         31.          0.6412624] tensor(8297.9980)\n",
      "[1.0000000e+00 7.3400000e+02 1.0000000e+00 1.0000000e+00 4.1000000e+01\n",
      " 1.2300000e+02 0.0000000e+00 2.0000000e+00 0.0000000e+00 0.0000000e+00\n",
      " 0.0000000e+00 0.0000000e+00 0.0000000e+00 3.1000000e+01 5.1998844e-01] tensor(8000.)\n",
      "[  2.         162.           0.           1.          39.\n",
      " 121.           1.           0.           0.           0.\n",
      "   0.           0.           0.          33.           1.89400483] tensor(16800.2344)\n",
      "[1.00000000e+00 4.65000000e+02 0.00000000e+00 1.00000000e+00\n",
      " 2.60000000e+01 1.07000000e+02 0.00000000e+00 2.00000000e+00\n",
      " 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00\n",
      " 0.00000000e+00 3.30000000e+01 2.00470543e-01] tensor(7288.6064)\n",
      "[8.00000000e+00 6.35000000e+02 0.00000000e+00 1.00000000e+00\n",
      " 4.20000000e+01 8.60000000e+01 0.00000000e+00 0.00000000e+00\n",
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      " 0.00000000e+00 3.10000000e+01 4.24233531e-01] tensor(7776.9434)\n",
      "[ 2.00000000e+00  7.34000000e+02  1.00000000e+00  1.00000000e+00\n",
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      "  0.00000000e+00  3.30000000e+01 -2.48496109e-02] tensor(6830.9341)\n",
      "[  1.         840.           0.           1.          26.\n",
      " 106.           0.           2.           0.           0.\n",
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      "[   2.         1703.            0.            0.           29.\n",
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      "[  1.         841.           0.           1.          30.\n",
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      "[  1.         837.           0.           1.          32.\n",
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      "[  1.         874.           0.           1.          31.\n",
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      "[ 4.00000000e+00  1.70300000e+03  0.00000000e+00  0.00000000e+00\n",
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      " 0.00000000e+00 3.10000000e+01 1.11436842e+00] tensor(9718.1426)\n",
      "[  2.          54.           0.           1.          30.\n",
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      " 0.00000000e+00 2.40000000e+01 1.11436842e+00] tensor(9718.1426)\n",
      "[  1.         200.           0.           1.          39.\n",
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      "  0.00000000e+00  3.30000000e+01 -2.48496109e-02] tensor(6830.9341)\n",
      "[  1.          28.           0.           1.          25.\n",
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      "[  2.         743.           0.           1.          36.\n",
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      "[ 12.         290.           0.           1.          31.\n",
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      "   0.           0.           0.          29.          -1.29818526] tensor(4268.)\n",
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      "  0.00000000e+00  3.30000000e+01 -2.46441106e-01] tensor(6402.)\n",
      "[  2.        734.          1.          1.         45.        126.\n",
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      "[  2.         844.           0.           1.          39.\n",
      " 116.           0.           2.           0.           0.\n",
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      "[  1.         837.           0.           1.          34.\n",
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      "   0.           0.           0.          33.          -1.04358761] tensor(4859.0713)\n",
      "[ 1.00000000e+00  7.34000000e+02  1.00000000e+00  1.00000000e+00\n",
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      "  0.00000000e+00  2.90000000e+01 -2.46441106e-01] tensor(6402.)\n",
      "[  1.         362.           0.           1.          28.\n",
      " 115.           0.           2.           3.           3.\n",
      "   0.           0.           0.          28.           0.73256683] tensor(8536.)\n",
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      " 0.00000000e+00 3.10000000e+01 1.43569229e-01] tensor(7170.3403)\n",
      "[  1.         160.           1.           1.          30.\n",
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      "[   2.         1703.            0.            0.           43.\n",
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      "[  1.         363.           0.           1.          36.\n",
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      "[ 2.         26.          0.          1.         42.         86.\n",
      "  0.          0.          0.          0.          0.          0.\n",
      "  0.         33.         -0.70677457] tensor(5531.9990)\n",
      "[1.0000000e+00 8.5100000e+02 0.0000000e+00 1.0000000e+00 2.3000000e+01\n",
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      " 0.0000000e+00 0.0000000e+00 0.0000000e+00 3.3000000e+01 5.1998844e-01] tensor(8000.)\n",
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      " 0.0000000e+00 0.0000000e+00 0.0000000e+00 3.3000000e+01 1.2775747e+00] tensor(10369.2578)\n",
      "[ 2.00000000e+00  8.52000000e+02  0.00000000e+00  1.00000000e+00\n",
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      "  0.00000000e+00  1.10000000e+01 -2.48496109e-02] tensor(6830.9341)\n",
      "[3.00000000e+00 2.85000000e+02 0.00000000e+00 1.00000000e+00\n",
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      "[ 2.00000000e+00  1.70300000e+03  0.00000000e+00  0.00000000e+00\n",
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      "[  1.          10.           0.           1.          26.\n",
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      "[  2.         554.           1.           1.          42.\n",
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      "  0.00000000e+00  3.10000000e+01 -4.59278471e-01] tensor(6000.)\n",
      "[  2.         734.           1.           1.          28.\n",
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      "[ 2.00000000e+00  1.70300000e+03  0.00000000e+00  0.00000000e+00\n",
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      "[  1.         407.           1.           1.          39.\n",
      " 116.           0.           2.           3.           3.\n",
      "   0.           0.           0.          33.           1.58881165] tensor(12147.6777)\n",
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      "[  1.         407.           1.           1.          34.\n",
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      "[  1.           9.           0.           1.          39.\n",
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      "[ 1.00000000e+00  5.40000000e+01  0.00000000e+00  1.00000000e+00\n",
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     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "  0.00000000e+00  3.00000000e+01 -2.48496109e-02] tensor(6830.9341)\n",
      "[  1.         649.           0.           1.          42.\n",
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      "[  2.         260.           0.           1.          34.\n",
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      "[1.2000000e+01 1.7030000e+03 0.0000000e+00 0.0000000e+00 3.0000000e+01\n",
      " 1.2100000e+02 0.0000000e+00 2.0000000e+00 3.0000000e+00 3.0000000e+00\n",
      " 0.0000000e+00 0.0000000e+00 0.0000000e+00 2.9000000e+01 1.2775747e+00] tensor(10369.2578)\n",
      "[ 1.00000000e+00  4.07000000e+02  1.00000000e+00  1.00000000e+00\n",
      "  3.70000000e+01  1.12000000e+02  0.00000000e+00  2.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  3.10000000e+01 -2.48496109e-02] tensor(6830.9341)\n",
      "[  2.         160.           1.           1.          25.\n",
      " 118.           1.           0.           0.           0.\n",
      "   0.           0.           0.          33.          -0.70677457] tensor(5531.9990)\n",
      "[2.00000000e+00 6.35000000e+02 0.00000000e+00 1.00000000e+00\n",
      " 3.10000000e+01 1.20000000e+02 1.00000000e+00 0.00000000e+00\n",
      " 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00\n",
      " 0.00000000e+00 2.60000000e+01 4.24233531e-01] tensor(7776.9434)\n",
      "[ 2.00000000e+00  1.44800000e+03  0.00000000e+00  1.00000000e+00\n",
      "  4.20000000e+01  8.60000000e+01  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  3.10000000e+01 -7.06774568e-01] tensor(5531.9990)\n",
      "[  1.         840.           0.           1.          22.\n",
      " 113.           0.           2.           0.           0.\n",
      "   0.           0.           0.          30.           1.11436842] tensor(9718.1426)\n",
      "[  1.          57.           0.           1.          36.\n",
      " 117.           0.           2.           0.           0.\n",
      "   0.           0.           0.          30.          -0.70677457] tensor(5531.9990)\n",
      "[  1.         151.           0.           1.          42.\n",
      "  86.           0.           0.           0.           0.\n",
      "   0.           0.           0.          24.          -1.04358761] tensor(4859.0713)\n",
      "[1.00000000e+00 1.70300000e+03 0.00000000e+00 0.00000000e+00\n",
      " 3.60000000e+01 1.17000000e+02 0.00000000e+00 2.00000000e+00\n",
      " 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00\n",
      " 0.00000000e+00 3.30000000e+01 1.18880493e+00] tensor(10000.)\n",
      "[  4.         839.           0.           1.          32.\n",
      " 119.           1.           0.           0.           0.\n",
      "   0.           0.           0.          33.          -1.29818526] tensor(4268.)\n",
      "[ 1.00000000e+00  6.58000000e+02  0.00000000e+00  1.00000000e+00\n",
      "  4.20000000e+01  8.60000000e+01  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  2.90000000e+01 -5.11043371e-01] tensor(5902.6431)\n",
      "[  1.          28.           0.           1.          36.\n",
      " 114.           0.           2.           0.           0.\n",
      "   0.           0.           0.          18.          -1.18132525] tensor(4553.9561)\n",
      "[ 2.00000000e+00  8.51000000e+02  0.00000000e+00  1.00000000e+00\n",
      "  2.80000000e+01  1.13000000e+02  1.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  2.90000000e+01 -5.11043371e-01] tensor(5902.6431)\n",
      "[  1.         837.           0.           1.          27.\n",
      " 120.           0.           2.           0.           0.\n",
      "   0.           0.           0.          33.           0.84684595] tensor(8853.9639)\n",
      "[ 2.00000000e+00  8.06000000e+02  0.00000000e+00  1.00000000e+00\n",
      "  4.00000000e+01  1.14000000e+02  0.00000000e+00  2.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  1.90000000e+01 -5.11043371e-01] tensor(5902.6431)\n",
      "[  1.         407.           1.           1.          28.\n",
      " 113.           0.           2.           0.           0.\n",
      "   0.           0.           0.          33.           0.84684595] tensor(8853.9639)\n",
      "[  1.         160.           1.           1.          28.\n",
      " 115.           0.           2.           0.           0.\n",
      "   0.           0.           0.          30.           0.84684595] tensor(8853.9639)\n",
      "[  1.         407.           1.           1.          30.\n",
      " 114.           0.           2.           3.           3.\n",
      "   0.           0.           3.          25.           0.42423353] tensor(7776.9434)\n",
      "[ 12.         837.           0.           1.          31.\n",
      " 121.           0.           2.           3.           3.\n",
      "   0.           0.           3.          31.           1.93654839] tensor(19126.8828)\n",
      "[  2.         852.           0.           1.          36.\n",
      " 100.           1.           0.           0.           0.\n",
      "   0.           0.           0.          33.          -1.04358761] tensor(4859.0713)\n",
      "[2.00000000e+00 8.52000000e+02 0.00000000e+00 1.00000000e+00\n",
      " 2.90000000e+01 1.20000000e+02 1.00000000e+00 0.00000000e+00\n",
      " 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00\n",
      " 0.00000000e+00 3.10000000e+01 4.24233531e-01] tensor(7776.9434)\n",
      "[2.00000000e+00 1.24500000e+03 0.00000000e+00 1.00000000e+00\n",
      " 3.10000000e+01 1.07000000e+02 1.00000000e+00 0.00000000e+00\n",
      " 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00\n",
      " 0.00000000e+00 3.00000000e+01 8.46845955e-01] tensor(8853.9639)\n",
      "[1.00000000e+00 1.70300000e+03 0.00000000e+00 0.00000000e+00\n",
      " 3.40000000e+01 1.12000000e+02 0.00000000e+00 2.00000000e+00\n",
      " 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00\n",
      " 0.00000000e+00 3.30000000e+01 1.18880493e+00] tensor(10000.)\n",
      "[2.00000000e+00 1.70300000e+03 0.00000000e+00 0.00000000e+00\n",
      " 3.40000000e+01 1.14000000e+02 1.00000000e+00 0.00000000e+00\n",
      " 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00\n",
      " 0.00000000e+00 3.10000000e+01 1.93654839e+00] tensor(19126.8828)\n",
      "[ 2.00000000e+00  1.59000000e+02  1.00000000e+00  1.00000000e+00\n",
      "  1.90000000e+01  1.08000000e+02  0.00000000e+00  2.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  3.30000000e+01 -2.48496109e-02] tensor(6830.9341)\n",
      "[  2.         554.           1.           1.          34.\n",
      " 108.           0.           2.           0.           0.\n",
      "   0.           0.           0.          33.           1.58881165] tensor(12147.6777)\n",
      "[1.00000000e+00 1.70300000e+03 0.00000000e+00 0.00000000e+00\n",
      " 4.40000000e+01 8.60000000e+01 0.00000000e+00 2.00000000e+00\n",
      " 3.00000000e+00 3.00000000e+00 0.00000000e+00 0.00000000e+00\n",
      " 0.00000000e+00 3.30000000e+01 2.00470543e-01] tensor(7288.6064)\n",
      "[  2.         200.           0.           1.          42.\n",
      "  86.           0.           0.           0.           0.\n",
      "   0.           0.           0.          33.          -0.24644111] tensor(6402.)\n",
      "[  1.         160.           1.           1.          42.\n",
      "  86.           0.           0.           0.           0.\n",
      "   0.           0.           0.          29.           1.86966682] tensor(16005.)\n",
      "[  2.         748.           0.           1.          29.\n",
      " 119.           1.           0.           0.           0.\n",
      "   0.           0.           0.          33.          -1.18132525] tensor(4553.9561)\n",
      "[ 2.00000000e+00  1.70300000e+03  0.00000000e+00  0.00000000e+00\n",
      "  2.80000000e+01  1.15000000e+02  1.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  3.30000000e+01 -1.39501774e+00] tensor(4000.)\n",
      "[ 1.00000000e+00  6.37000000e+02  0.00000000e+00  0.00000000e+00\n",
      "  2.20000000e+01  1.13000000e+02  0.00000000e+00  2.00000000e+00\n",
      "  3.00000000e+00  3.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  3.00000000e+00  3.00000000e+01 -8.13051736e-02] tensor(6720.0938)\n",
      "[  2.         257.           1.           1.          42.\n",
      "  86.           0.           0.           0.           0.\n",
      "   0.           0.           0.          33.           1.68158211] tensor(12961.5723)\n",
      "[  1.          57.           0.           1.          32.\n",
      " 112.           0.           2.           0.           0.\n",
      "   0.           0.           0.          31.          -0.24644111] tensor(6402.)\n",
      "[  2.         773.           0.           0.          24.\n",
      " 118.           1.           0.           0.           0.\n",
      "   0.           0.           0.          33.          -0.88503262] tensor(5184.6289)\n",
      "[1.00000000e+00 2.57000000e+02 1.00000000e+00 1.00000000e+00\n",
      " 4.50000000e+01 1.26000000e+02 0.00000000e+00 2.00000000e+00\n",
      " 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00\n",
      " 0.00000000e+00 3.30000000e+01 2.00470543e-01] tensor(7288.6064)\n",
      "[  2.         167.           0.           1.          23.\n",
      " 113.           1.           0.           0.           0.\n",
      "   0.           0.           0.          33.           1.82760652] tensor(15000.)\n",
      "[  1.         159.           1.           1.          36.\n",
      " 114.           0.           2.           0.           0.\n",
      "   0.           0.           0.          33.          -1.04358761] tensor(4859.0713)\n",
      "[ 2.00000000e+00  6.52000000e+02  0.00000000e+00  1.00000000e+00\n",
      "  2.80000000e+01  1.13000000e+02  0.00000000e+00  2.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  3.00000000e+01 -4.59278471e-01] tensor(6000.)\n",
      "[  2.           9.           0.           1.          28.\n",
      " 112.           1.           0.           0.           0.\n",
      "   0.           0.           0.          33.          -1.39501774] tensor(4000.)\n",
      "[ 1.00000000e+00  6.52000000e+02  0.00000000e+00  1.00000000e+00\n",
      "  2.30000000e+01  1.13000000e+02  0.00000000e+00  2.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  3.30000000e+01 -2.48496109e-02] tensor(6830.9341)\n",
      "[  2.         257.           1.           1.          36.\n",
      " 117.           1.           0.           0.           0.\n",
      "   0.           0.           0.          31.           1.11436842] tensor(9718.1426)\n",
      "[ 2.00000000e+00  1.70300000e+03  0.00000000e+00  0.00000000e+00\n",
      "  3.10000000e+01  1.17000000e+02  1.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  2.90000000e+01 -1.18132525e+00] tensor(4553.9561)\n",
      "[ 1.00000000e+00  1.70300000e+03  0.00000000e+00  0.00000000e+00\n",
      "  4.30000000e+01  1.25000000e+02  0.00000000e+00  2.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  3.30000000e+01 -8.85032618e-01] tensor(5184.6289)\n",
      "[1.00000000e+00 6.52000000e+02 0.00000000e+00 1.00000000e+00\n",
      " 3.40000000e+01 1.13000000e+02 0.00000000e+00 2.00000000e+00\n",
      " 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00\n",
      " 0.00000000e+00 3.30000000e+01 6.41262404e-01] tensor(8297.9980)\n",
      "[  2.         530.           0.           1.          23.\n",
      " 113.           1.           0.           0.           0.\n",
      "   0.           0.           0.          33.          -1.04358761] tensor(4859.0713)\n",
      "[1.00000000e+00 1.70300000e+03 0.00000000e+00 0.00000000e+00\n",
      " 4.60000000e+01 1.25000000e+02 0.00000000e+00 2.00000000e+00\n",
      " 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00\n",
      " 0.00000000e+00 3.30000000e+01 2.00470543e-01] tensor(7288.6064)\n",
      "[  2.         407.           1.           1.          34.\n",
      " 112.           0.           2.           0.           0.\n",
      "   0.           0.           0.          31.           1.20889385] tensor(10080.1406)\n",
      "[  1.         841.           0.           1.          35.\n",
      " 113.           0.           2.           0.           0.\n",
      "   0.           0.           0.          31.           1.18880493] tensor(10000.)\n",
      "[  1.         842.           0.           1.          31.\n",
      " 107.           0.           2.           0.           0.\n",
      "   0.           0.           0.          30.          -0.88503262] tensor(5184.6289)\n",
      "[2.00000000e+00 8.52000000e+02 0.00000000e+00 1.00000000e+00\n",
      " 2.80000000e+01 1.12000000e+02 0.00000000e+00 2.00000000e+00\n",
      " 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00\n",
      " 0.00000000e+00 3.00000000e+01 8.46845955e-01] tensor(8853.9639)\n",
      "[  1.         840.           0.           1.          42.\n",
      "  86.           0.           0.           0.           0.\n",
      "   0.           0.           0.          29.           1.36054634] tensor(10755.5107)\n",
      "[  1.         159.           1.           1.          45.\n",
      " 126.           0.           2.           3.           3.\n",
      "   4.           0.           3.          30.           1.72544904] tensor(13440.1875)\n",
      "[  2.      159.        1.        1.       23.      112.        0.\n",
      "   2.        0.        0.        0.        0.        0.       30.\n",
      "   0.58742] tensor(8163.3535)\n",
      "[  1.         225.           0.           1.          32.\n",
      " 117.           0.           2.           0.           0.\n",
      "   0.           0.           0.          16.           0.84684595] tensor(8853.9639)\n",
      "[  1.         160.           1.           1.          29.\n",
      " 106.           0.           2.           0.           0.\n",
      "   0.           0.           0.          12.          -1.39501774] tensor(4000.)\n",
      "[  2.         944.           0.           1.          43.\n",
      " 126.           1.           0.           0.           0.\n",
      "   0.           0.           0.          33.          -1.29818526] tensor(4268.)\n",
      "[  2.         852.           0.           1.          39.\n",
      " 121.           1.           0.           0.           0.\n",
      "   0.           0.           0.          29.           1.34300582] tensor(10670.)\n",
      "[  1.         160.           1.           1.          39.\n",
      " 121.           0.           2.           0.           0.\n",
      "   0.           0.           0.          33.          -1.18132525] tensor(4553.9561)\n",
      "[  1.          28.           0.           1.          39.\n",
      " 116.           0.           2.           0.           0.\n",
      "   0.           0.           0.          31.          -1.29818526] tensor(4268.)\n",
      "[1.0000000e+00 7.6400000e+02 0.0000000e+00 1.0000000e+00 3.0000000e+01\n",
      " 1.2000000e+02 0.0000000e+00 2.0000000e+00 0.0000000e+00 0.0000000e+00\n",
      " 0.0000000e+00 0.0000000e+00 0.0000000e+00 3.3000000e+01 5.1998844e-01] tensor(8000.)\n",
      "[  1.         159.           1.           1.          42.\n",
      "  86.           0.           0.           0.           0.\n",
      "   0.           0.           0.          27.          -0.30114386] tensor(6298.1201)\n",
      "[  1.         869.           0.           1.          38.\n",
      " 121.           0.           2.           0.           0.\n",
      "   0.           0.           0.          33.          -1.29818526] tensor(4268.)\n",
      "[2.00000000e+00 8.51000000e+02 0.00000000e+00 1.00000000e+00\n",
      " 3.60000000e+01 1.17000000e+02 0.00000000e+00 2.00000000e+00\n",
      " 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00\n",
      " 0.00000000e+00 2.60000000e+01 2.00470543e-01] tensor(7288.6064)\n",
      "[ 2.00000000e+00  8.52000000e+02  0.00000000e+00  1.00000000e+00\n",
      "  2.40000000e+01  1.17000000e+02  1.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  3.30000000e+01 -5.11043371e-01] tensor(5902.6431)\n",
      "[ 2.00000000e+00  1.23500000e+03  0.00000000e+00  1.00000000e+00\n",
      "  2.30000000e+01  1.13000000e+02  1.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  3.10000000e+01 -1.04358761e+00] tensor(4859.0713)\n",
      "[ 2.00000000e+00  1.70300000e+03  0.00000000e+00  0.00000000e+00\n",
      "  4.20000000e+01  8.60000000e+01  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  3.10000000e+01 -2.46441106e-01] tensor(6402.)\n",
      "[ 2.00000000e+00  1.46000000e+03  0.00000000e+00  0.00000000e+00\n",
      "  2.80000000e+01  1.12000000e+02  1.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  3.10000000e+01 -3.01143857e-01] tensor(6298.1201)\n",
      "[  1.        635.          0.          1.         36.        120.\n",
      "   0.          2.          0.          0.          0.          0.\n",
      "   0.         33.          1.2775747] tensor(10369.2578)\n",
      "[  2.         311.           0.           1.          36.\n",
      " 116.           0.           2.           0.           0.\n",
      "   0.           0.           0.          23.          -1.29818526] tensor(4268.)\n",
      "[  1.         159.           1.           1.          28.\n",
      " 112.           0.           2.           3.           3.\n",
      "   0.           0.           0.          33.           1.97065282] tensor(28462.2246)\n",
      "[  2.         410.           0.           1.          25.\n",
      " 114.           1.           0.           0.           0.\n",
      "   0.           0.           0.          30.           0.93187116] tensor(9107.9121)\n",
      "[  1.         151.           0.           1.          22.\n",
      " 108.           0.           2.           0.           0.\n",
      "   0.           0.           0.          12.           0.20047054] tensor(7288.6064)\n",
      "[  2.           9.           0.           1.          32.\n",
      " 118.           1.           0.           0.           0.\n",
      "   0.           0.           0.          33.           0.84684595] tensor(8853.9639)\n",
      "[  1.         848.           0.           1.          38.\n",
      " 121.           0.           2.           0.           0.\n",
      "   0.           0.           0.          24.          -1.04358761] tensor(4859.0713)\n",
      "[2.00000000e+00 7.18000000e+02 0.00000000e+00 1.00000000e+00\n",
      " 4.20000000e+01 8.60000000e+01 0.00000000e+00 0.00000000e+00\n",
      " 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00\n",
      " 0.00000000e+00 3.30000000e+01 4.24233531e-01] tensor(7776.9434)\n",
      "[ 1.00000000e+00  8.52000000e+02  0.00000000e+00  1.00000000e+00\n",
      "  3.00000000e+01  1.03000000e+02  0.00000000e+00  2.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  2.70000000e+01 -3.01143857e-01] tensor(6298.1201)\n",
      "[  2.         407.           1.           1.          30.\n",
      " 114.           0.           2.           0.           0.\n",
      "   0.           0.           0.          29.           0.42423353] tensor(7776.9434)\n",
      "[  1.         852.           0.           1.          24.\n",
      " 118.           0.           2.           0.           0.\n",
      "   0.           0.           0.          30.          -1.29818526] tensor(4268.)\n",
      "[  2.         407.           1.           1.          30.\n",
      " 114.           0.           2.           0.           0.\n",
      "   0.           0.           0.          33.          -0.70677457] tensor(5531.9990)\n",
      "[  1.         754.           0.           1.          42.\n",
      "  86.           0.           0.           0.           0.\n",
      "   0.           0.           0.          33.          -0.88503262] tensor(5184.6289)\n",
      "[1.00000000e+00 3.73000000e+02 0.00000000e+00 1.00000000e+00\n",
      " 3.10000000e+01 1.17000000e+02 0.00000000e+00 2.00000000e+00\n",
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      "[  1.         735.           0.           1.          28.\n",
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      "[  2.         554.           1.           1.          43.\n",
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      "[  1.         847.           0.           1.          32.\n",
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      "[  2.         652.           0.           1.          43.\n",
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      "[  1.         554.           1.           1.          36.\n",
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      "[ 11.         646.           0.           1.          39.\n",
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      " 0.00000000e+00 3.30000000e+01 8.46845955e-01] tensor(8853.9639)\n",
      "[ 2.00000000e+00  1.70300000e+03  0.00000000e+00  0.00000000e+00\n",
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      "  0.00000000e+00  3.00000000e+01 -1.39501774e+00] tensor(4000.)\n",
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      "[  2.         10.          0.          1.         33.        119.\n",
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      "[  2.         160.           1.           1.          22.\n",
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      "[  1.         160.           1.           1.          32.\n",
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      "[  2.         310.           0.           1.          32.\n",
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     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "  3.00000000e+00  3.30000000e+01 -8.85032618e-01] tensor(5184.6289)\n",
      "[  1.         635.           0.           1.          39.\n",
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      " 3.40000000e+01 1.08000000e+02 0.00000000e+00 2.00000000e+00\n",
      " 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00\n",
      " 0.00000000e+00 3.10000000e+01 4.24233531e-01] tensor(7776.9434)\n",
      "[ 2.00000000e+00  7.34000000e+02  1.00000000e+00  1.00000000e+00\n",
      "  3.40000000e+01  1.13000000e+02  0.00000000e+00  2.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  3.30000000e+01 -2.48496109e-02] tensor(6830.9341)\n",
      "[2.00000000e+00 7.34000000e+02 1.00000000e+00 1.00000000e+00\n",
      " 3.10000000e+01 1.18000000e+02 1.00000000e+00 0.00000000e+00\n",
      " 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00\n",
      " 0.00000000e+00 2.90000000e+01 7.32566829e-01] tensor(8536.)\n",
      "[ 2.00000000e+00  1.70300000e+03  0.00000000e+00  0.00000000e+00\n",
      "  4.10000000e+01  1.23000000e+02  0.00000000e+00  2.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  2.60000000e+01 -3.01143857e-01] tensor(6298.1201)\n",
      "[ 2.         54.          0.          1.         42.         86.\n",
      "  0.          0.          0.          0.          0.          0.\n",
      "  0.         31.          1.11436842] tensor(9718.1426)\n",
      "[  2.         411.           0.           1.          42.\n",
      "  86.           0.           0.           0.           0.\n",
      "   0.           0.           0.          33.          -0.51104337] tensor(5902.6431)\n",
      "[2.00000000e+00 8.51000000e+02 0.00000000e+00 1.00000000e+00\n",
      " 2.30000000e+01 1.13000000e+02 1.00000000e+00 0.00000000e+00\n",
      " 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00\n",
      " 0.00000000e+00 3.00000000e+01 8.46845955e-01] tensor(8853.9639)\n",
      "[  1.         260.           0.           1.          43.\n",
      " 126.           1.           0.           0.           0.\n",
      "   0.           0.           0.          33.          -0.88503262] tensor(5184.6289)\n",
      "[  2.         652.           0.           1.          36.\n",
      " 117.           0.           2.           0.           0.\n",
      "   0.           0.           0.          33.          -0.88503262] tensor(5184.6289)\n",
      "[  2.         310.           0.           1.          33.\n",
      " 119.           1.           0.           0.           0.\n",
      "   0.           0.           0.          26.          -0.51104337] tensor(5902.6431)\n",
      "[  1.         311.           0.           1.          34.\n",
      " 108.           0.           2.           0.           0.\n",
      "   0.           0.           0.          33.           0.84684595] tensor(8853.9639)\n",
      "[  1.         840.           0.           1.          30.\n",
      " 114.           0.           2.           0.           0.\n",
      "   0.           0.           0.          31.          -1.29818526] tensor(4268.)\n",
      "[ 2.00000000e+00  7.34000000e+02  1.00000000e+00  1.00000000e+00\n",
      "  3.10000000e+01  1.20000000e+02  1.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  3.30000000e+01 -2.48496109e-02] tensor(6830.9341)\n",
      "[  1.         734.           1.           1.          40.\n",
      " 111.           0.           2.           0.           0.\n",
      "   0.           0.           0.          16.           1.89400483] tensor(16800.2344)\n",
      "[ 1.00000000e+00  7.48000000e+02  0.00000000e+00  1.00000000e+00\n",
      "  2.90000000e+01  1.13000000e+02  0.00000000e+00  2.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  3.30000000e+01 -3.01143857e-01] tensor(6298.1201)\n",
      "[  1.           9.           0.           1.          26.\n",
      " 100.           0.           2.           3.           3.\n",
      "   0.           0.           0.          31.          -0.88503262] tensor(5184.6289)\n",
      "[  2.         160.           1.           1.          23.\n",
      " 100.           0.           2.           0.           0.\n",
      "   0.           0.           0.          13.          -1.29818526] tensor(4268.)\n",
      "[  1.         407.           1.           1.          39.\n",
      " 119.           0.           2.           0.           0.\n",
      "   0.           0.           0.          29.           0.99069543] tensor(9293.8887)\n",
      "[  2.         160.           1.           1.          27.\n",
      " 109.           1.           0.           0.           0.\n",
      "   0.           0.           0.          28.          -0.51104337] tensor(5902.6431)\n",
      "[  1.         747.           0.           1.          29.\n",
      " 104.           0.           2.           0.           0.\n",
      "   0.           0.           0.          31.          -1.29818526] tensor(4268.)\n",
      "[  1.         841.           0.           1.          30.\n",
      " 109.           0.           2.           0.           0.\n",
      "   0.           0.           0.          31.          -0.88503262] tensor(5184.6289)\n",
      "[3.00000000e+00 1.70300000e+03 0.00000000e+00 0.00000000e+00\n",
      " 4.20000000e+01 8.60000000e+01 0.00000000e+00 0.00000000e+00\n",
      " 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00\n",
      " 0.00000000e+00 3.30000000e+01 2.00470543e-01] tensor(7288.6064)\n",
      "[  1.         944.           0.           1.          36.\n",
      " 114.           0.           2.           0.           0.\n",
      "   0.           0.           0.          31.           1.58881165] tensor(12147.6777)\n",
      "[2.00000000e+00 1.70300000e+03 0.00000000e+00 0.00000000e+00\n",
      " 4.20000000e+01 8.60000000e+01 0.00000000e+00 0.00000000e+00\n",
      " 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00\n",
      " 0.00000000e+00 3.30000000e+01 7.32566829e-01] tensor(8536.)\n",
      "[  1.         159.           1.           1.          30.\n",
      " 114.           0.           2.           3.           3.\n",
      "   0.           0.           0.          33.           1.86015571] tensor(15745.2998)\n",
      "[  1.         235.           0.           1.          30.\n",
      " 114.           0.           2.           0.           0.\n",
      "   0.           0.           0.          30.           1.47629237] tensor(11384.8896)\n",
      "[  1.        159.          1.          1.         31.        117.\n",
      "   0.          2.          0.          0.          0.          0.\n",
      "   0.         31.          1.2775747] tensor(10369.2578)\n",
      "[  2.        734.          1.          1.         31.        121.\n",
      "   0.          2.          3.          0.          0.          0.\n",
      "   0.         29.          1.2775747] tensor(10369.2578)\n",
      "[  7.         753.           0.           1.          42.\n",
      "  86.           0.           0.           0.           0.\n",
      "   0.           0.           0.          31.           1.11436842] tensor(9718.1426)\n",
      "[  2.         841.           0.           1.          21.\n",
      " 111.           1.           0.           0.           0.\n",
      "   0.           0.           0.          30.          -1.18132525] tensor(4553.9561)\n",
      "[  2.         160.           1.           1.          23.\n",
      " 113.           1.           0.           0.           0.\n",
      "   0.           0.           0.          30.          -0.24644111] tensor(6402.)\n",
      "[  1.         159.           1.           1.          42.\n",
      "  86.           0.           0.           0.           0.\n",
      "   0.           0.           0.          29.          -0.51104337] tensor(5902.6431)\n",
      "[  1.         178.           0.           1.          38.\n",
      " 114.           0.           2.           0.           0.\n",
      "   0.           0.           0.          33.          -1.04358761] tensor(4859.0713)\n",
      "[  1.         236.           0.           1.          39.\n",
      " 117.           0.           2.           3.           3.\n",
      "   0.           0.           3.          19.          -1.04358761] tensor(4859.0713)\n",
      "[  1.         406.           0.           1.          27.\n",
      " 120.           0.           2.           0.           0.\n",
      "   0.           0.           0.          19.          -1.04358761] tensor(4859.0713)\n",
      "[  1.         166.           0.           1.          42.\n",
      "  86.           0.           0.           0.           0.\n",
      "   0.           0.           0.          29.           1.94012006] tensor(19442.3574)\n",
      "[  1.         311.           0.           1.          34.\n",
      " 108.           0.           2.           0.           0.\n",
      "   0.           0.           0.          29.           0.73256683] tensor(8536.)\n",
      "[ 1.00000000e+00  8.40000000e+02  0.00000000e+00  1.00000000e+00\n",
      "  2.50000000e+01  1.10000000e+02  0.00000000e+00  2.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  3.10000000e+01 -7.06774568e-01] tensor(5531.9990)\n",
      "[ 1.00000000e+00  9.44000000e+02  0.00000000e+00  1.00000000e+00\n",
      "  3.90000000e+01  1.16000000e+02  0.00000000e+00  2.00000000e+00\n",
      "  3.00000000e+00  3.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  3.00000000e+00  3.10000000e+01 -2.48496109e-02] tensor(6830.9341)\n",
      "[  4.         311.           0.           1.          26.\n",
      " 117.           0.           2.           0.           0.\n",
      "   0.           0.           0.          30.           1.68158211] tensor(12961.5723)\n",
      "[  1.          45.           0.           1.          22.\n",
      " 108.           0.           2.           0.           0.\n",
      "   0.           0.           0.          30.           0.79629725] tensor(8710.2979)\n",
      "[ 1.00000000e+00  7.34000000e+02  1.00000000e+00  1.00000000e+00\n",
      "  4.20000000e+01  8.60000000e+01  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  2.90000000e+01 -2.48496109e-02] tensor(6830.9341)\n",
      "[ 2.00000000e+00  4.11000000e+02  0.00000000e+00  1.00000000e+00\n",
      "  3.00000000e+01  1.09000000e+02  0.00000000e+00  2.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  2.80000000e+01 -2.46441106e-01] tensor(6402.)\n",
      "[  2.         260.           0.           1.          36.\n",
      " 101.           1.           0.           0.           0.\n",
      "   0.           0.           0.          33.          -0.30114386] tensor(6298.1201)\n",
      "[2.00000000e+00 4.10000000e+02 0.00000000e+00 1.00000000e+00\n",
      " 4.20000000e+01 8.60000000e+01 0.00000000e+00 0.00000000e+00\n",
      " 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00\n",
      " 0.00000000e+00 3.30000000e+01 2.00470543e-01] tensor(7288.6064)\n",
      "[2.00000000e+00 1.70300000e+03 0.00000000e+00 0.00000000e+00\n",
      " 2.80000000e+01 1.12000000e+02 1.00000000e+00 0.00000000e+00\n",
      " 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00\n",
      " 0.00000000e+00 3.00000000e+01 1.34300582e+00] tensor(10670.)\n",
      "[1.00000000e+00 6.49000000e+02 0.00000000e+00 1.00000000e+00\n",
      " 3.40000000e+01 1.08000000e+02 0.00000000e+00 2.00000000e+00\n",
      " 3.00000000e+00 3.00000000e+00 0.00000000e+00 0.00000000e+00\n",
      " 0.00000000e+00 3.30000000e+01 4.24233531e-01] tensor(7776.9434)\n",
      "[ 12.         238.           0.           1.          39.\n",
      " 116.           0.           2.           3.           0.\n",
      "   0.           0.           0.          28.           0.73256683] tensor(8536.)\n",
      "[  2.         714.           0.           1.          30.\n",
      " 114.           1.           0.           0.           0.\n",
      "   0.           0.           0.          33.          -1.39501774] tensor(4000.)\n",
      "[  1.         814.           0.           1.          30.\n",
      " 114.           0.           2.           3.           3.\n",
      "   0.           0.           0.          33.          -1.18132525] tensor(4553.9561)\n",
      "[  2.         159.           1.           1.          34.\n",
      " 113.           0.           2.           0.           0.\n",
      "   0.           0.           0.          33.          -0.51104337] tensor(5902.6431)\n",
      "[  1.        160.          1.          1.         30.        103.\n",
      "   0.          2.          3.          3.          0.          0.\n",
      "   3.         31.          1.2775747] tensor(10369.2578)\n",
      "[  2.         554.           1.           1.          45.\n",
      " 126.           1.           0.           0.           0.\n",
      "   0.           0.           0.          33.          -0.88503262] tensor(5184.6289)\n",
      "[4.00000000e+00 8.40000000e+02 0.00000000e+00 1.00000000e+00\n",
      " 4.20000000e+01 8.60000000e+01 0.00000000e+00 0.00000000e+00\n",
      " 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00\n",
      " 0.00000000e+00 3.30000000e+01 2.00470543e-01] tensor(7288.6064)\n",
      "[  1.        159.          1.          1.         42.         86.\n",
      "   0.          0.          0.          0.          0.          0.\n",
      "   0.         29.          1.9010312] tensor(17077.3359)\n",
      "[  1.         748.           0.           1.          30.\n",
      " 114.           0.           2.           0.           0.\n",
      "   0.           0.           0.          33.           1.42012124] tensor(11063.9980)\n",
      "[ 2.00000000e+00  6.29000000e+02  0.00000000e+00  1.00000000e+00\n",
      "  4.20000000e+01  8.60000000e+01  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  2.90000000e+01 -3.01143857e-01] tensor(6298.1201)\n",
      "[ 1.00000000e+00  5.30000000e+02  0.00000000e+00  1.00000000e+00\n",
      "  2.30000000e+01  1.13000000e+02  0.00000000e+00  2.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  2.90000000e+01 -4.59278471e-01] tensor(6000.)\n",
      "[ 2.00000000e+00  1.19900000e+03  0.00000000e+00  1.00000000e+00\n",
      "  4.20000000e+01  8.60000000e+01  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  3.30000000e+01 -1.04358761e+00] tensor(4859.0713)\n",
      "[  1.         735.           0.           1.          29.\n",
      " 104.           0.           2.           0.           0.\n",
      "   0.           0.           0.          28.           1.11436842] tensor(9718.1426)\n",
      "[ 2.00000000e+00  1.70300000e+03  0.00000000e+00  0.00000000e+00\n",
      "  4.00000000e+01  1.11000000e+02  1.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  9.00000000e+00 -7.06774568e-01] tensor(5531.9990)\n",
      "[1.00000000e+00 8.40000000e+02 0.00000000e+00 1.00000000e+00\n",
      " 4.10000000e+01 1.23000000e+02 0.00000000e+00 2.00000000e+00\n",
      " 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00\n",
      " 0.00000000e+00 2.40000000e+01 3.68223674e-01] tensor(7650.7529)\n",
      "[  2.        160.          1.          1.         42.         86.\n",
      "   0.          0.          0.          0.          0.          0.\n",
      "   0.         29.          1.2775747] tensor(10369.2578)\n",
      "[1.0000000e+00 1.7030000e+03 0.0000000e+00 0.0000000e+00 3.2000000e+01\n",
      " 1.1900000e+02 0.0000000e+00 2.0000000e+00 0.0000000e+00 0.0000000e+00\n",
      " 0.0000000e+00 0.0000000e+00 0.0000000e+00 2.6000000e+01 5.1998844e-01] tensor(8000.)\n",
      "[  2.         658.           0.           1.          34.\n",
      " 109.           0.           2.           0.           0.\n",
      "   0.           0.           0.          33.          -1.18132525] tensor(4553.9561)\n",
      "[ 1.00000000e+00  1.70300000e+03  0.00000000e+00  0.00000000e+00\n",
      "  3.60000000e+01  1.17000000e+02  0.00000000e+00  2.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  8.00000000e+00 -1.18132525e+00] tensor(4553.9561)\n",
      "[  1.         554.           1.           1.          34.\n",
      " 113.           0.           2.           3.           3.\n",
      "   0.           0.           0.          33.           1.64302154] tensor(12596.2402)\n",
      "[ 2.00000000e+00  8.53000000e+02  0.00000000e+00  1.00000000e+00\n",
      "  3.00000000e+01  1.20000000e+02  1.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  2.80000000e+01 -8.13051736e-02] tensor(6720.0938)\n",
      "[  1.         407.           1.           1.          43.\n",
      " 125.           0.           2.           0.           0.\n",
      "   0.           0.           0.          31.          -1.04358761] tensor(4859.0713)\n",
      "[  2.         160.           1.           1.          30.\n",
      " 114.           1.           0.           0.           0.\n",
      "   0.           0.           0.          21.          -1.29818526] tensor(4268.)\n",
      "[  2.           9.           0.           1.          23.\n",
      " 113.           1.           0.           0.           0.\n",
      "   0.           0.           0.          30.          -1.29818526] tensor(4268.)\n",
      "[ 12.         806.           0.           1.          23.\n",
      " 113.           0.           2.           0.           0.\n",
      "   0.           0.           0.          31.          -1.39501774] tensor(4000.)\n",
      "[  2.         159.           1.           1.          45.\n",
      " 126.           0.           2.           0.           0.\n",
      "   0.           0.           0.          31.          -1.39501774] tensor(4000.)\n",
      "[1.00000000e+00 8.42000000e+02 0.00000000e+00 1.00000000e+00\n",
      " 3.10000000e+01 1.20000000e+02 0.00000000e+00 2.00000000e+00\n",
      " 3.00000000e+00 3.00000000e+00 0.00000000e+00 0.00000000e+00\n",
      " 0.00000000e+00 2.60000000e+01 4.24233531e-01] tensor(7776.9434)\n",
      "[ 2.00000000e+00  4.10000000e+02  0.00000000e+00  1.00000000e+00\n",
      "  3.40000000e+01  1.13000000e+02  0.00000000e+00  2.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  3.30000000e+01 -3.01143857e-01] tensor(6298.1201)\n",
      "[  1.         840.           0.           1.          39.\n",
      " 116.           0.           2.           3.           3.\n",
      "   0.           0.           3.          19.           1.42012124] tensor(11063.9980)\n",
      "[  1.         719.           0.           1.          30.\n",
      " 114.           0.           2.           0.           0.\n",
      "   0.           0.           0.          30.           0.93187116] tensor(9107.9121)\n",
      "[  1.         716.           0.           1.          35.\n",
      " 113.           0.           2.           0.           0.\n",
      "   0.           0.           0.          33.          -1.04358761] tensor(4859.0713)\n",
      "[ 2.00000000e+00  1.70300000e+03  0.00000000e+00  0.00000000e+00\n",
      "  3.20000000e+01  1.18000000e+02  1.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  2.60000000e+01 -1.18132525e+00] tensor(4553.9561)\n",
      "[1.00000000e+00 1.70300000e+03 0.00000000e+00 0.00000000e+00\n",
      " 3.20000000e+01 1.19000000e+02 0.00000000e+00 2.00000000e+00\n",
      " 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00\n",
      " 0.00000000e+00 2.60000000e+01 1.18880493e+00] tensor(10000.)\n",
      "[ 2.00000000e+00  1.70300000e+03  0.00000000e+00  0.00000000e+00\n",
      "  3.00000000e+01  1.03000000e+02  1.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  3.10000000e+01 -7.06774568e-01] tensor(5531.9990)\n",
      "[2.00000000e+00 1.19900000e+03 0.00000000e+00 1.00000000e+00\n",
      " 3.00000000e+01 1.03000000e+02 1.00000000e+00 0.00000000e+00\n",
      " 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00\n",
      " 0.00000000e+00 5.00000000e+00 1.18880493e+00] tensor(10000.)\n",
      "[1.00000000e+00 8.42000000e+02 0.00000000e+00 1.00000000e+00\n",
      " 2.70000000e+01 1.12000000e+02 0.00000000e+00 2.00000000e+00\n",
      " 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00\n",
      " 0.00000000e+00 1.70000000e+01 2.00470543e-01] tensor(7288.6064)\n",
      "[  1.         348.           0.           1.          29.\n",
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      "   0.           0.           3.          30.           1.34300582] tensor(10670.)\n",
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      "  0.00000000e+00  2.70000000e+01 -2.46441106e-01] tensor(6402.)\n",
      "[ 1.00000000e+00  7.47000000e+02  0.00000000e+00  1.00000000e+00\n",
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      "  0.00000000e+00  3.30000000e+01 -8.13051736e-02] tensor(6720.0938)\n",
      "[ 1.00000000e+00  7.48000000e+02  0.00000000e+00  1.00000000e+00\n",
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      "  0.00000000e+00  3.10000000e+01 -2.46441106e-01] tensor(6402.)\n",
      "[1.0000000e+00 1.7030000e+03 0.0000000e+00 0.0000000e+00 3.9000000e+01\n",
      " 1.1600000e+02 0.0000000e+00 2.0000000e+00 0.0000000e+00 0.0000000e+00\n",
      " 0.0000000e+00 0.0000000e+00 0.0000000e+00 3.1000000e+01 5.1998844e-01] tensor(8000.)\n",
      "[ 1.00000000e+00  4.07000000e+02  1.00000000e+00  1.00000000e+00\n",
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      "  0.00000000e+00  2.60000000e+01 -2.48496109e-02] tensor(6830.9341)\n",
      "[ 2.00000000e+00  1.51500000e+03  0.00000000e+00  1.00000000e+00\n",
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      "  0.00000000e+00  3.00000000e+01 -7.06774568e-01] tensor(5531.9990)\n",
      "[ 2.00000000e+00  1.70300000e+03  0.00000000e+00  0.00000000e+00\n",
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      "  0.00000000e+00  3.10000000e+01 -1.18132525e+00] tensor(4553.9561)\n",
      "[ 1.00000000e+00  8.42000000e+02  0.00000000e+00  1.00000000e+00\n",
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      "  3.00000000e+00  1.70000000e+01 -7.06774568e-01] tensor(5531.9990)\n",
      "[  2.         530.           0.           1.          31.\n",
      " 120.           1.           0.           0.           0.\n",
      "   0.           0.           0.          33.          -1.29818526] tensor(4268.)\n",
      "[ 1.00000000e+00  6.49000000e+02  0.00000000e+00  1.00000000e+00\n",
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      "  0.00000000e+00  3.10000000e+01 -8.13051736e-02] tensor(6720.0938)\n",
      "[  1.         257.           1.           1.          32.\n",
      " 118.           0.           2.           0.           0.\n",
      "   0.           0.           0.          26.          -0.51104337] tensor(5902.6431)\n",
      "[2.00000000e+00 9.44000000e+02 0.00000000e+00 1.00000000e+00\n",
      " 3.70000000e+01 1.21000000e+02 1.00000000e+00 0.00000000e+00\n",
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      " 0.00000000e+00 2.30000000e+01 2.00470543e-01] tensor(7288.6064)\n",
      "[  2.         554.           1.           1.          34.\n",
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      "[  2.         739.           0.           1.          36.\n",
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      "[  2.         840.           0.           1.          24.\n",
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      "   0.           0.           0.          30.           1.58881165] tensor(12147.6777)\n",
      "[ 1.00000000e+00  1.60000000e+02  1.00000000e+00  1.00000000e+00\n",
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      "  0.00000000e+00  2.30000000e+01 -2.48496109e-02] tensor(6830.9341)\n",
      "[ 2.00000000e+00  8.37000000e+02  0.00000000e+00  1.00000000e+00\n",
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      "  0.00000000e+00  3.30000000e+01 -3.01143857e-01] tensor(6298.1201)\n",
      "[  1.         160.           1.           1.          36.\n",
      " 116.           0.           2.           0.           0.\n",
      "   0.           0.           0.          33.          -1.39501774] tensor(4000.)\n",
      "[  1.         311.           0.           1.          43.\n",
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      "  0.00000000e+00  2.80000000e+01 -4.59278471e-01] tensor(6000.)\n",
      "[ 12.         749.           0.           1.          39.\n",
      " 116.           0.           2.           3.           3.\n",
      "   0.           0.           0.          31.           1.60126778] tensor(12245.0303)\n",
      "[ 2.00000000e+00  1.70300000e+03  0.00000000e+00  0.00000000e+00\n",
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      "  0.00000000e+00  2.20000000e+01 -1.18132525e+00] tensor(4553.9561)\n",
      "[  1.         865.           0.           1.          29.\n",
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      "[  2.         162.           0.           1.          42.\n",
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      "[  1.         407.           1.           1.          34.\n",
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      "[  1.         649.           0.           1.          34.\n",
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      "   0.           0.           0.          33.           0.93187116] tensor(9107.9121)\n",
      "[ 2.00000000e+00  1.70300000e+03  0.00000000e+00  0.00000000e+00\n",
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      "  0.00000000e+00  3.00000000e+01 -7.06774568e-01] tensor(5531.9990)\n",
      "[ 2.00000000e+00  1.44800000e+03  0.00000000e+00  1.00000000e+00\n",
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      "  0.00000000e+00  3.00000000e+01 -2.48496109e-02] tensor(6830.9341)\n",
      "[1.00000000e+00 5.92000000e+02 0.00000000e+00 1.00000000e+00\n",
      " 3.80000000e+01 1.12000000e+02 0.00000000e+00 2.00000000e+00\n",
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      " 0.00000000e+00 1.60000000e+01 2.00470543e-01] tensor(7288.6064)\n",
      "[  1.         311.           0.           1.          30.\n",
      " 114.           0.           2.           3.           3.\n",
      "   0.           0.           3.          33.           1.72544904] tensor(13440.1875)\n",
      "[ 1.00000000e+00  4.07000000e+02  1.00000000e+00  1.00000000e+00\n",
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      "  0.00000000e+00  1.60000000e+01 -2.46441106e-01] tensor(6402.)\n",
      "[ 2.00000000e+00  1.70300000e+03  0.00000000e+00  0.00000000e+00\n",
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      "  0.00000000e+00  3.00000000e+01 -1.18132525e+00] tensor(4553.9561)\n",
      "[  2.         629.           0.           1.          43.\n",
      " 126.           0.           2.           0.           0.\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "   0.           0.           0.          31.           1.97065282] tensor(28462.2246)\n",
      "[  1.         842.           0.           1.          23.\n",
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      "[  2.         168.           0.           1.          23.\n",
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      "[  2.         162.           0.           1.          28.\n",
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      "[  1.         771.           0.           1.          30.\n",
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      "[  2.         261.           0.           1.          30.\n",
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      "[  2.         407.           1.           1.          30.\n",
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      "[ 2.00000000e+00  1.78000000e+02  0.00000000e+00  1.00000000e+00\n",
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      "[  1.           9.           0.           1.          41.\n",
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      "   0.           0.           0.          33.          -1.39501774] tensor(4000.)\n",
      "[  1.         534.           0.           1.          39.\n",
      " 116.           0.           2.           0.           0.\n",
      "   0.           0.           0.          31.          -1.29818526] tensor(4268.)\n",
      "[  2.         554.           1.           1.          30.\n",
      " 106.           1.           0.           0.           0.\n",
      "   0.           0.           0.          27.          -0.88503262] tensor(5184.6289)\n",
      "[2.00000000e+00 8.52000000e+02 0.00000000e+00 1.00000000e+00\n",
      " 2.70000000e+01 1.13000000e+02 0.00000000e+00 2.00000000e+00\n",
      " 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00\n",
      " 0.00000000e+00 3.30000000e+01 4.24233531e-01] tensor(7776.9434)\n",
      "[ 11.         239.           1.           1.          42.\n",
      "  86.           0.           0.           0.           0.\n",
      "   0.           0.           0.          33.           1.92387304] tensor(18221.5156)\n",
      "[  2.         359.           0.           1.          22.\n",
      " 114.           1.           0.           0.           0.\n",
      "   0.           0.           0.          30.           0.42423353] tensor(7776.9434)\n",
      "[  1.         754.           0.           1.          33.\n",
      " 120.           0.           2.           0.           0.\n",
      "   0.           0.           0.          31.           1.94012006] tensor(19442.3574)\n",
      "[ 2.00000000e+00  1.70300000e+03  0.00000000e+00  0.00000000e+00\n",
      "  3.80000000e+01  1.21000000e+02  1.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  3.10000000e+01 -1.29818526e+00] tensor(4268.)\n",
      "[  2.         840.           0.           1.          39.\n",
      " 116.           0.           2.           0.           0.\n",
      "   0.           0.           0.          31.          -1.18132525] tensor(4553.9561)\n",
      "[  1.         160.           1.           1.          40.\n",
      " 120.           0.           2.           0.           0.\n",
      "   0.           0.           0.          33.          -1.29818526] tensor(4268.)\n",
      "[ 2.00000000e+00  7.34000000e+02  1.00000000e+00  1.00000000e+00\n",
      "  4.20000000e+01  8.60000000e+01  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  3.30000000e+01 -3.01143857e-01] tensor(6298.1201)\n",
      "[   2.         1703.            0.            0.           42.\n",
      "   86.            0.            0.            0.            0.\n",
      "    0.            0.            0.           33.            1.94894891] tensor(20408.3848)\n",
      "[ 12.         311.           0.           1.          39.\n",
      " 116.           0.           2.           3.           3.\n",
      "   0.           0.           0.          33.           1.96709287] tensor(25000.)\n",
      "[  1.         722.           0.           0.          46.\n",
      " 130.           0.           2.           0.           0.\n",
      "   0.           0.           0.          22.          -1.04358761] tensor(4859.0713)\n",
      "[1.00000000e+00 7.19000000e+02 0.00000000e+00 1.00000000e+00\n",
      " 4.40000000e+01 1.29000000e+02 0.00000000e+00 2.00000000e+00\n",
      " 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00\n",
      " 0.00000000e+00 3.10000000e+01 2.00470543e-01] tensor(7288.6064)\n",
      "[ 2.00000000e+00  1.70300000e+03  0.00000000e+00  0.00000000e+00\n",
      "  2.80000000e+01  1.13000000e+02  1.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  3.30000000e+01 -1.18132525e+00] tensor(4553.9561)\n",
      "[  2.         734.           1.           1.          35.\n",
      " 120.           1.           0.           0.           0.\n",
      "   0.           0.           0.          33.          -0.88503262] tensor(5184.6289)\n",
      "[ 3.00000000e+00  7.12000000e+02  0.00000000e+00  1.00000000e+00\n",
      "  2.80000000e+01  1.16000000e+02  1.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  3.30000000e+01 -2.46441106e-01] tensor(6402.)\n",
      "[  1.         841.           0.           1.          29.\n",
      " 106.           0.           2.           0.           0.\n",
      "   0.           0.           0.          31.          -1.04358761] tensor(4859.0713)\n",
      "[  1.          49.           0.           1.          33.\n",
      " 116.           0.           2.           0.           0.\n",
      "   0.           0.           0.          20.          -0.51104337] tensor(5902.6431)\n",
      "[  1.         798.           0.           0.          27.\n",
      " 118.           0.           2.           0.           0.\n",
      "   0.           0.           0.          33.          -1.18132525] tensor(4553.9561)\n",
      "[  1.         407.           1.           1.          32.\n",
      " 118.           0.           2.           3.           0.\n",
      "   0.           0.           0.          31.           1.36054634] tensor(10755.5107)\n",
      "[  2.         554.           1.           1.          34.\n",
      " 108.           0.           2.           0.           0.\n",
      "   0.           0.           0.          11.          -1.18132525] tensor(4553.9561)\n",
      "[  2.         260.           0.           1.          29.\n",
      " 113.           1.           0.           0.           0.\n",
      "   0.           0.           0.          33.           1.68158211] tensor(12961.5723)\n",
      "[ 2.00000000e+00  9.44000000e+02  0.00000000e+00  1.00000000e+00\n",
      "  3.20000000e+01  1.17000000e+02  1.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  2.00000000e+01 -4.59278471e-01] tensor(6000.)\n",
      "[ 2.00000000e+00  1.70300000e+03  0.00000000e+00  0.00000000e+00\n",
      "  3.20000000e+01  1.18000000e+02  1.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  2.60000000e+01 -5.11043371e-01] tensor(5902.6431)\n",
      "[ 2.00000000e+00  1.51800000e+03  0.00000000e+00  1.00000000e+00\n",
      "  3.10000000e+01  1.04000000e+02  0.00000000e+00  2.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  2.90000000e+01 -1.29818526e+00] tensor(4268.)\n",
      "[ 1.20000000e+01  6.52000000e+02  0.00000000e+00  1.00000000e+00\n",
      "  3.10000000e+01  1.21000000e+02  0.00000000e+00  2.00000000e+00\n",
      "  3.00000000e+00  3.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  3.30000000e+01 -3.01143857e-01] tensor(6298.1201)\n",
      "[  1.         543.           0.           1.          36.\n",
      " 116.           0.           2.           0.           0.\n",
      "   0.           0.           0.          31.          -1.29818526] tensor(4268.)\n",
      "[  1.         734.           1.           1.          46.\n",
      " 130.           0.           2.           0.           0.\n",
      "   0.           0.           0.          15.           0.84684595] tensor(8853.9639)\n",
      "[ 1.00000000e+00  7.48000000e+02  0.00000000e+00  1.00000000e+00\n",
      "  4.50000000e+01  1.26000000e+02  0.00000000e+00  2.00000000e+00\n",
      "  3.00000000e+00  3.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  3.10000000e+01 -2.48496109e-02] tensor(6830.9341)\n",
      "[  1.        407.          1.          1.         34.        108.\n",
      "   0.          2.          0.          0.          0.          0.\n",
      "   0.         33.          1.2775747] tensor(10369.2578)\n",
      "[ 12.         652.           0.           1.          39.\n",
      " 116.           0.           2.           3.           0.\n",
      "   0.           0.           0.          31.          -0.70677457] tensor(5531.9990)\n",
      "[  2.         162.           0.           1.          23.\n",
      " 116.           1.           0.           0.           0.\n",
      "   0.           0.           0.          30.          -1.04358761] tensor(4859.0713)\n",
      "[1.00000000e+00 1.70300000e+03 0.00000000e+00 0.00000000e+00\n",
      " 3.40000000e+01 1.08000000e+02 0.00000000e+00 2.00000000e+00\n",
      " 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00\n",
      " 0.00000000e+00 3.30000000e+01 2.00470543e-01] tensor(7288.6064)\n",
      "[ 1.00000000e+00  7.20000000e+02  0.00000000e+00  1.00000000e+00\n",
      "  3.00000000e+01  1.15000000e+02  0.00000000e+00  2.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  2.80000000e+01 -2.48496109e-02] tensor(6830.9341)\n",
      "[  1.         649.           0.           1.          42.\n",
      "  86.           0.           0.           0.           0.\n",
      "   0.           0.           0.          33.           1.03704191] tensor(9447.1797)\n",
      "[ 2.00000000e+00  1.70300000e+03  0.00000000e+00  0.00000000e+00\n",
      "  4.20000000e+01  8.60000000e+01  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  3.30000000e+01 -1.18132525e+00] tensor(4553.9561)\n",
      "[ 1.00000000e+00  4.07000000e+02  1.00000000e+00  1.00000000e+00\n",
      "  4.20000000e+01  8.60000000e+01  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  3.30000000e+01 -2.48496109e-02] tensor(6830.9341)\n",
      "[  1.         660.           0.           1.          30.\n",
      " 104.           0.           2.           0.           0.\n",
      "   0.           0.           0.          33.          -1.29818526] tensor(4268.)\n",
      "[ 2.00000000e+00  7.34000000e+02  1.00000000e+00  1.00000000e+00\n",
      "  3.00000000e+01  1.14000000e+02  1.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  3.30000000e+01 -3.01143857e-01] tensor(6298.1201)\n",
      "[  2.          54.           0.           1.          41.\n",
      " 117.           0.           2.           0.           0.\n",
      "   0.           0.           0.          33.           1.11436842] tensor(9718.1426)\n",
      "[  2.         197.           0.           1.          26.\n",
      " 117.           0.           2.           0.           0.\n",
      "   0.           0.           0.          33.          -0.70677457] tensor(5531.9990)\n",
      "[  1.        748.          0.          1.         36.        114.\n",
      "   0.          2.          0.          0.          0.          0.\n",
      "   0.         30.          1.2775747] tensor(10369.2578)\n",
      "[  2.         554.           1.           1.          30.\n",
      " 117.           0.           2.           0.           0.\n",
      "   0.           0.           0.          20.           1.58881165] tensor(12147.6777)\n",
      "[ 1.00000000e+00  9.44000000e+02  0.00000000e+00  1.00000000e+00\n",
      "  3.00000000e+01  1.03000000e+02  0.00000000e+00  2.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  2.70000000e+01 -7.06774568e-01] tensor(5531.9990)\n",
      "[  1.         944.           0.           1.          23.\n",
      " 113.           0.           2.           3.           3.\n",
      "   0.           0.           0.          31.           1.18880493] tensor(10000.)\n",
      "[ 1.00000000e+00  4.89000000e+02  0.00000000e+00  1.00000000e+00\n",
      "  4.30000000e+01  1.26000000e+02  0.00000000e+00  2.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  3.30000000e+01 -3.01143857e-01] tensor(6298.1201)\n",
      "[  1.         407.           1.           1.          41.\n",
      " 123.           0.           2.           3.           3.\n",
      "   0.           0.           0.          24.          -0.70677457] tensor(5531.9990)\n",
      "[  2.         764.           0.           1.          28.\n",
      " 112.           0.           2.           0.           0.\n",
      "   0.           0.           0.          17.           0.79629725] tensor(8710.2979)\n",
      "[ 2.00000000e+00  2.85000000e+02  0.00000000e+00  1.00000000e+00\n",
      "  3.40000000e+01  1.08000000e+02  0.00000000e+00  2.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  3.30000000e+01 -2.48496109e-02] tensor(6830.9341)\n",
      "[  1.         407.           1.           1.          39.\n",
      " 116.           0.           2.           3.           3.\n",
      "   4.           5.           3.          31.           1.96709287] tensor(25000.)\n",
      "[ 1.00000000e+00  8.70000000e+02  0.00000000e+00  1.00000000e+00\n",
      "  2.80000000e+01  1.12000000e+02  0.00000000e+00  2.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  2.80000000e+01 -3.01143857e-01] tensor(6298.1201)\n",
      "[1.00000000e+00 1.70300000e+03 0.00000000e+00 0.00000000e+00\n",
      " 4.60000000e+01 1.26000000e+02 0.00000000e+00 2.00000000e+00\n",
      " 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00\n",
      " 0.00000000e+00 3.30000000e+01 9.31871161e-01] tensor(9107.9121)\n",
      "[4.00000000e+00 1.70300000e+03 0.00000000e+00 0.00000000e+00\n",
      " 4.20000000e+01 8.60000000e+01 0.00000000e+00 0.00000000e+00\n",
      " 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00\n",
      " 0.00000000e+00 3.00000000e+01 8.46845955e-01] tensor(8853.9639)\n",
      "[  1.        749.          0.          1.         23.        113.\n",
      "   0.          2.          0.          0.          0.          0.\n",
      "   0.         30.          1.9010312] tensor(17077.3359)\n",
      "[  2.         260.           0.           1.          28.\n",
      " 112.           1.           0.           0.           0.\n",
      "   0.           0.           0.          30.          -0.45927847] tensor(6000.)\n",
      "[2.00000000e+00 1.70300000e+03 0.00000000e+00 0.00000000e+00\n",
      " 4.00000000e+01 1.20000000e+02 0.00000000e+00 2.00000000e+00\n",
      " 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00\n",
      " 0.00000000e+00 3.30000000e+01 1.36054634e+00] tensor(10755.5107)\n",
      "[ 1.00000000e+00  8.70000000e+02  0.00000000e+00  1.00000000e+00\n",
      "  3.80000000e+01  1.15000000e+02  0.00000000e+00  2.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  3.30000000e+01 -2.48496109e-02] tensor(6830.9341)\n",
      "[ 2.00000000e+00  1.64600000e+03  0.00000000e+00  1.00000000e+00\n",
      "  3.00000000e+01  1.03000000e+02  0.00000000e+00  2.00000000e+00\n",
      "  3.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  1.70000000e+01 -5.11043371e-01] tensor(5902.6431)\n",
      "[ 1.00000000e+00  7.68000000e+02  0.00000000e+00  0.00000000e+00\n",
      "  4.20000000e+01  8.60000000e+01  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  3.30000000e+01 -7.06774568e-01] tensor(5531.9990)\n",
      "[ 2.00000000e+00  7.34000000e+02  1.00000000e+00  1.00000000e+00\n",
      "  3.50000000e+01  1.14000000e+02  1.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  3.30000000e+01 -2.46441106e-01] tensor(6402.)\n",
      "[  1.         166.           0.           1.          42.\n",
      "  86.           0.           0.           0.           0.\n",
      "   0.           0.           0.          30.          -0.24644111] tensor(6402.)\n",
      "[ 1.00000000e+00  7.36000000e+02  0.00000000e+00  1.00000000e+00\n",
      "  3.90000000e+01  1.16000000e+02  0.00000000e+00  2.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  2.90000000e+01 -3.01143857e-01] tensor(6298.1201)\n",
      "[  1.         348.           0.           1.          29.\n",
      " 105.           0.           2.           0.           0.\n",
      "   0.           0.           0.          33.          -0.51104337] tensor(5902.6431)\n",
      "[1.00000000e+00 1.70300000e+03 0.00000000e+00 0.00000000e+00\n",
      " 3.90000000e+01 1.16000000e+02 0.00000000e+00 2.00000000e+00\n",
      " 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00\n",
      " 0.00000000e+00 3.10000000e+01 1.60126778e+00] tensor(12245.0303)\n",
      "[ 1.00000000e+00  4.07000000e+02  1.00000000e+00  1.00000000e+00\n",
      "  2.80000000e+01  1.12000000e+02  0.00000000e+00  2.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  1.70000000e+01 -8.13051736e-02] tensor(6720.0938)\n",
      "[  1.         739.           0.           1.          34.\n",
      " 108.           0.           2.           0.           0.\n",
      "   0.           0.           0.          33.          -0.88503262] tensor(5184.6289)\n",
      "[  1.         310.           0.           1.          32.\n",
      " 118.           0.           2.           0.           0.\n",
      "   0.           0.           0.          33.          -1.04358761] tensor(4859.0713)\n",
      "[  2.         407.           1.           1.          42.\n",
      "  86.           0.           0.           0.           0.\n",
      "   0.           0.           0.          33.          -0.88503262] tensor(5184.6289)\n",
      "[ 1.00000000e+00  7.43000000e+02  0.00000000e+00  1.00000000e+00\n",
      "  3.10000000e+01  1.18000000e+02  0.00000000e+00  2.00000000e+00\n",
      "  3.00000000e+00  3.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  3.30000000e+01 -8.13051736e-02] tensor(6720.0938)\n",
      "[  1.         757.           0.           1.          26.\n",
      " 119.           0.           2.           0.           0.\n",
      "   0.           0.           0.          33.          -1.04358761] tensor(4859.0713)\n",
      "[ 1.00000000e+00  6.49000000e+02  0.00000000e+00  1.00000000e+00\n",
      "  2.20000000e+01  1.13000000e+02  0.00000000e+00  2.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  3.30000000e+01 -4.59278471e-01] tensor(6000.)\n",
      "[  2.         734.           1.           1.          30.\n",
      " 103.           0.           2.           0.           0.\n",
      "   0.           0.           0.          31.           1.20889385] tensor(10080.1406)\n",
      "[  1.           9.           0.           1.          28.\n",
      " 112.           0.           2.           0.           0.\n",
      "   0.           0.           0.          33.           0.51998844] tensor(8000.)\n",
      "[ 1.00000000e+00  1.70300000e+03  0.00000000e+00  0.00000000e+00\n",
      "  3.90000000e+01  1.19000000e+02  0.00000000e+00  2.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  3.30000000e+01 -2.48496109e-02] tensor(6830.9341)\n",
      "[  1.         749.           0.           1.          31.\n",
      " 117.           0.           2.           0.           0.\n",
      "   0.           0.           0.          20.          -1.18132525] tensor(4553.9561)\n",
      "[  1.         407.           1.           1.          30.\n",
      " 114.           0.           2.           0.           0.\n",
      "   0.           0.           0.          30.           1.96929153] tensor(26675.)\n",
      "[ 2.00000000e+00  1.70300000e+03  0.00000000e+00  0.00000000e+00\n",
      "  3.50000000e+01  1.14000000e+02  1.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  1.80000000e+01 -1.39501774e+00] tensor(4000.)\n",
      "[1.00000000e+00 6.35000000e+02 0.00000000e+00 1.00000000e+00\n",
      " 3.00000000e+01 1.20000000e+02 0.00000000e+00 2.00000000e+00\n",
      " 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00\n",
      " 0.00000000e+00 2.80000000e+01 1.43569229e-01] tensor(7170.3403)\n",
      "[ 2.00000000e+00  1.45000000e+03  0.00000000e+00  1.00000000e+00\n",
      "  3.60000000e+01  1.03000000e+02  1.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  2.90000000e+01 -7.06774568e-01] tensor(5531.9990)\n",
      "[  2.         844.           0.           1.          36.\n",
      " 116.           1.           0.           0.           0.\n",
      "   0.           0.           0.          23.          -0.88503262] tensor(5184.6289)\n",
      "[  2.         865.           0.           1.          42.\n",
      "  86.           0.           0.           0.           0.\n",
      "   0.           0.           0.          31.           1.34300582] tensor(10670.)\n",
      "[ 2.00000000e+00  9.44000000e+02  0.00000000e+00  1.00000000e+00\n",
      "  3.80000000e+01  1.15000000e+02  1.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  3.10000000e+01 -7.06774568e-01] tensor(5531.9990)\n",
      "[  1.         373.           0.           1.          28.\n",
      " 115.           0.           2.           0.           0.\n",
      "   0.           0.           0.          33.          -0.88503262] tensor(5184.6289)\n",
      "[  1.         348.           0.           1.          39.\n",
      " 116.           0.           2.           3.           0.\n",
      "   0.           0.           0.          33.           0.84684595] tensor(8853.9639)\n",
      "[  1.         543.           0.           1.          34.\n",
      " 112.           0.           2.           0.           0.\n",
      "   0.           0.           0.          18.          -1.18132525] tensor(4553.9561)\n",
      "[  1.         652.           0.           1.          32.\n",
      " 118.           0.           2.           0.           0.\n",
      "   0.           0.           0.          31.          -0.88503262] tensor(5184.6289)\n",
      "[ 2.00000000e+00  6.58000000e+02  0.00000000e+00  1.00000000e+00\n",
      "  3.90000000e+01  1.16000000e+02  0.00000000e+00  2.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  3.30000000e+01 -3.01143857e-01] tensor(6298.1201)\n",
      "[1.00000000e+00 8.74000000e+02 0.00000000e+00 1.00000000e+00\n",
      " 3.10000000e+01 1.21000000e+02 0.00000000e+00 2.00000000e+00\n",
      " 3.00000000e+00 3.00000000e+00 0.00000000e+00 0.00000000e+00\n",
      " 3.00000000e+00 2.90000000e+01 2.00470543e-01] tensor(7288.6064)\n",
      "[ 1.00000000e+00  1.70300000e+03  0.00000000e+00  0.00000000e+00\n",
      "  3.20000000e+01  1.17000000e+02  0.00000000e+00  2.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  2.00000000e+01 -7.06774568e-01] tensor(5531.9990)\n",
      "[  2.         410.           0.           1.          22.\n",
      " 111.           1.           0.           0.           0.\n",
      "   0.           0.           0.          30.          -1.29818526] tensor(4268.)\n",
      "[ 2.00000000e+00  3.10000000e+02  0.00000000e+00  1.00000000e+00\n",
      "  2.80000000e+01  1.13000000e+02  1.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  3.30000000e+01 -3.01143857e-01] tensor(6298.1201)\n",
      "[ 1.00000000e+00  7.53000000e+02  0.00000000e+00  1.00000000e+00\n",
      "  3.70000000e+01  1.21000000e+02  0.00000000e+00  2.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  3.30000000e+01 -2.46441106e-01] tensor(6402.)\n",
      "[ 2.00000000e+00  1.70300000e+03  0.00000000e+00  0.00000000e+00\n",
      "  4.00000000e+01  1.11000000e+02  0.00000000e+00  2.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  3.30000000e+01 -1.29818526e+00] tensor(4268.)\n",
      "[  2.         543.           0.           1.          41.\n",
      " 121.           1.           0.           0.           0.\n",
      "   0.           0.           0.          30.          -1.18132525] tensor(4553.9561)\n",
      "[ 4.00000000e+00  9.00000000e+00  0.00000000e+00  1.00000000e+00\n",
      "  4.20000000e+01  8.60000000e+01  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  2.90000000e+01 -8.13051736e-02] tensor(6720.0938)\n",
      "[  2.          57.           0.           1.          37.\n",
      " 121.           1.           0.           0.           0.\n",
      "   0.           0.           0.          23.          -1.29818526] tensor(4268.)\n",
      "[  1.         348.           0.           1.          23.\n",
      " 116.           0.           2.           0.           0.\n",
      "   0.           0.           0.          30.          -0.88503262] tensor(5184.6289)\n",
      "[ 3.00000000e+00  1.70300000e+03  0.00000000e+00  0.00000000e+00\n",
      "  4.00000000e+01  1.17000000e+02  1.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  3.10000000e+01 -2.48496109e-02] tensor(6830.9341)\n",
      "[ 1.00000000e+00  4.07000000e+02  1.00000000e+00  1.00000000e+00\n",
      "  2.50000000e+01  1.19000000e+02  0.00000000e+00  2.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  2.10000000e+01 -3.01143857e-01] tensor(6298.1201)\n",
      "[  1.        747.          0.          1.         36.        114.\n",
      "   0.          2.          0.          0.          0.          0.\n",
      "   0.         33.          1.2775747] tensor(10369.2578)\n",
      "[ 2.00000000e+00  8.51000000e+02  0.00000000e+00  1.00000000e+00\n",
      "  4.20000000e+01  8.60000000e+01  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  2.90000000e+01 -8.13051736e-02] tensor(6720.0938)\n",
      "[ 2.00000000e+00  8.51000000e+02  0.00000000e+00  1.00000000e+00\n",
      "  3.80000000e+01  1.14000000e+02  1.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  2.20000000e+01 -5.11043371e-01] tensor(5902.6431)\n",
      "[ 3.00000000e+00  7.29000000e+02  0.00000000e+00  1.00000000e+00\n",
      "  4.20000000e+01  8.60000000e+01  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  3.00000000e+01 -5.11043371e-01] tensor(5902.6431)\n",
      "[  1.         851.           0.           1.          23.\n",
      " 113.           0.           2.           0.           0.\n",
      "   0.           0.           0.          30.           1.11436842] tensor(9718.1426)\n",
      "[  2.         65.          0.          0.         38.        114.\n",
      "   0.          2.          0.          0.          0.          0.\n",
      "   0.         29.          0.6412624] tensor(8297.9980)\n",
      "[  1.         159.           1.           1.          46.\n",
      " 130.           0.           2.           0.           0.\n",
      "   0.           0.           0.          31.           1.94012006] tensor(19442.3574)\n",
      "[  2.         407.           1.           1.          27.\n",
      " 112.           1.           0.           0.           0.\n",
      "   0.           0.           0.          30.          -0.88503262] tensor(5184.6289)\n",
      "[ 1.00000000e+00  7.19000000e+02  0.00000000e+00  1.00000000e+00\n",
      "  3.90000000e+01  1.17000000e+02  0.00000000e+00  2.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  2.20000000e+01 -7.06774568e-01] tensor(5531.9990)\n",
      "[ 2.00000000e+00  1.70300000e+03  0.00000000e+00  0.00000000e+00\n",
      "  2.10000000e+01  1.08000000e+02  1.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  3.00000000e+01 -7.06774568e-01] tensor(5531.9990)\n",
      "[   2.        1703.           0.           0.          42.\n",
      "   86.           0.           0.           0.           0.\n",
      "    0.           0.           0.          33.           1.8803246] tensor(16326.7070)\n",
      "[ 3.00000000e+00  1.70300000e+03  0.00000000e+00  0.00000000e+00\n",
      "  4.20000000e+01  8.60000000e+01  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  3.10000000e+01 -2.46441106e-01] tensor(6402.)\n",
      "[2.00000000e+00 6.52000000e+02 0.00000000e+00 1.00000000e+00\n",
      " 4.20000000e+01 8.60000000e+01 0.00000000e+00 0.00000000e+00\n",
      " 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00\n",
      " 0.00000000e+00 3.30000000e+01 6.41262404e-01] tensor(8297.9980)\n",
      "[2.00000000e+00 1.70300000e+03 0.00000000e+00 0.00000000e+00\n",
      " 4.20000000e+01 1.18000000e+02 0.00000000e+00 2.00000000e+00\n",
      " 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00\n",
      " 0.00000000e+00 3.30000000e+01 1.58881165e+00] tensor(12147.6777)\n",
      "[ 1.00000000e+00  7.34000000e+02  1.00000000e+00  1.00000000e+00\n",
      "  4.20000000e+01  1.29000000e+02  0.00000000e+00  2.00000000e+00\n",
      "  3.00000000e+00  3.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  3.30000000e+01 -8.13051736e-02] tensor(6720.0938)\n",
      "[  1.         840.           0.           1.          32.\n",
      " 118.           0.           2.           3.           3.\n",
      "   0.           0.           0.          26.           0.84684595] tensor(8853.9639)\n",
      "[  1.         465.           0.           1.          26.\n",
      " 106.           0.           2.           3.           3.\n",
      "   0.           0.           0.          33.          -1.04358761] tensor(4859.0713)\n",
      "[  1.         159.           1.           1.          31.\n",
      " 121.           0.           2.           0.           0.\n",
      "   0.           0.           0.          33.           1.58881165] tensor(12147.6777)\n",
      "[  2.         712.           0.           1.          28.\n",
      " 120.           1.           0.           0.           0.\n",
      "   0.           0.           0.          28.          -1.04358761] tensor(4859.0713)\n",
      "[  2.         257.           1.           1.          30.\n",
      " 112.           1.           0.           0.           0.\n",
      "   0.           0.           0.          31.          -0.70677457] tensor(5531.9990)\n",
      "[  2.          10.           0.           1.          28.\n",
      " 115.           0.           2.           0.           0.\n",
      "   0.           0.           0.          33.          -1.04358761] tensor(4859.0713)\n",
      "[  1.         162.           0.           1.          29.\n",
      " 106.           0.           2.           0.           0.\n",
      "   0.           0.           0.          33.          -0.24644111] tensor(6402.)\n",
      "[  2.         852.           0.           1.          42.\n",
      "  86.           0.           0.           0.           0.\n",
      "   0.           0.           0.          28.           1.03704191] tensor(9447.1797)\n",
      "[1.00000000e+00 7.64000000e+02 0.00000000e+00 1.00000000e+00\n",
      " 3.30000000e+01 1.16000000e+02 0.00000000e+00 2.00000000e+00\n",
      " 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00\n",
      " 0.00000000e+00 3.00000000e+01 4.24233531e-01] tensor(7776.9434)\n",
      "[  1.         629.           0.           1.          30.\n",
      " 112.           0.           2.           0.           0.\n",
      "   0.           0.           0.          29.           0.73256683] tensor(8536.)\n",
      "[ 3.        54.         0.         1.        42.        86.\n",
      "  0.         0.         0.         0.         0.         0.\n",
      "  0.        31.         1.2775747] tensor(10369.2578)\n",
      "[  2.         837.           0.           1.          23.\n",
      " 113.           1.           0.           0.           0.\n",
      "   0.           0.           0.          31.          -1.29818526] tensor(4268.)\n",
      "[ 2.00000000e+00  7.54000000e+02  0.00000000e+00  1.00000000e+00\n",
      "  3.20000000e+01  1.18000000e+02  1.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  2.60000000e+01 -7.06774568e-01] tensor(5531.9990)\n",
      "[1.00000000e+00 4.07000000e+02 1.00000000e+00 1.00000000e+00\n",
      " 3.00000000e+01 1.20000000e+02 0.00000000e+00 2.00000000e+00\n",
      " 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00\n",
      " 0.00000000e+00 3.10000000e+01 2.00470543e-01] tensor(7288.6064)\n",
      "[  2.         764.           0.           1.          36.\n",
      " 120.           0.           2.           0.           0.\n",
      "   0.           0.           0.          23.          -0.88503262] tensor(5184.6289)\n",
      "[  2.        159.          1.          1.         28.        115.\n",
      "   1.          0.          0.          0.          0.          0.\n",
      "   0.         31.          0.6412624] tensor(8297.9980)\n",
      "[ 2.00000000e+00  1.62000000e+02  0.00000000e+00  1.00000000e+00\n",
      "  3.90000000e+01  1.19000000e+02  1.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  3.10000000e+01 -8.13051736e-02] tensor(6720.0938)\n",
      "[  1.         285.           0.           1.          30.\n",
      " 114.           0.           2.           3.           3.\n",
      "   0.           0.           0.          25.           1.72544904] tensor(13440.1875)\n",
      "[1.00000000e+00 7.16000000e+02 0.00000000e+00 1.00000000e+00\n",
      " 3.90000000e+01 1.16000000e+02 0.00000000e+00 2.00000000e+00\n",
      " 3.00000000e+00 3.00000000e+00 0.00000000e+00 0.00000000e+00\n",
      " 3.00000000e+00 3.10000000e+01 2.00470543e-01] tensor(7288.6064)\n",
      "[  1.         652.           0.           1.          36.\n",
      " 103.           0.           2.           0.           0.\n",
      "   0.           0.           0.          33.          -1.04358761] tensor(4859.0713)\n",
      "[  1.         734.           1.           1.          28.\n",
      " 116.           0.           2.           0.           0.\n",
      "   0.           0.           0.          33.          -1.39501774] tensor(4000.)\n",
      "[  2.        348.          0.          1.         42.         86.\n",
      "   0.          0.          0.          0.          0.          0.\n",
      "   0.         30.          1.2775747] tensor(10369.2578)\n",
      "[  2.           9.           0.           1.          30.\n",
      " 104.           1.           0.           0.           0.\n",
      "   0.           0.           0.          33.          -1.18132525] tensor(4553.9561)\n",
      "[  1.         160.           1.           1.          19.\n",
      " 108.           0.           2.           0.           0.\n",
      "   0.           0.           0.          33.          -1.04358761] tensor(4859.0713)\n",
      "[  2.         200.           0.           1.          45.\n",
      " 126.           0.           2.           0.           0.\n",
      "   0.           0.           0.          33.          -0.24644111] tensor(6402.)\n",
      "[  2.         851.           0.           1.          28.\n",
      " 115.           1.           0.           0.           0.\n",
      "   0.           0.           0.          30.          -0.88503262] tensor(5184.6289)\n",
      "[  2.         840.           0.           1.          22.\n",
      " 108.           0.           2.           0.           0.\n",
      "   0.           0.           0.          30.          -0.88503262] tensor(5184.6289)\n",
      "[  2.         162.           0.           1.          42.\n",
      "  86.           0.           0.           0.           0.\n",
      "   0.           0.           0.          33.           0.20047054] tensor(7288.6064)\n",
      "[ 2.00000000e+00  1.70300000e+03  0.00000000e+00  0.00000000e+00\n",
      "  3.40000000e+01  1.09000000e+02  1.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  3.30000000e+01 -2.48496109e-02] tensor(6830.9341)\n",
      "[  1.         289.           0.           1.          31.\n",
      " 120.           0.           2.           3.           3.\n",
      "   0.           0.           0.          33.          -1.18132525] tensor(4553.9561)\n",
      "[ 1.00000000e+00  6.35000000e+02  0.00000000e+00  1.00000000e+00\n",
      "  3.00000000e+01  1.14000000e+02  0.00000000e+00  2.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  3.30000000e+01 -2.48496109e-02] tensor(6830.9341)\n",
      "[1.00000000e+00 1.70300000e+03 0.00000000e+00 0.00000000e+00\n",
      " 4.20000000e+01 8.60000000e+01 0.00000000e+00 0.00000000e+00\n",
      " 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00\n",
      " 0.00000000e+00 3.30000000e+01 1.89400483e+00] tensor(16800.2344)\n",
      "[1.00000000e+00 4.07000000e+02 1.00000000e+00 1.00000000e+00\n",
      " 2.70000000e+01 1.13000000e+02 0.00000000e+00 2.00000000e+00\n",
      " 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00\n",
      " 0.00000000e+00 3.00000000e+01 2.00470543e-01] tensor(7288.6064)\n",
      "[ 2.00000000e+00  4.07000000e+02  1.00000000e+00  1.00000000e+00\n",
      "  3.40000000e+01  1.14000000e+02  1.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  3.10000000e+01 -2.46441106e-01] tensor(6402.)\n",
      "[  1.         159.           1.           1.          36.\n",
      " 116.           0.           2.           0.           0.\n",
      "   0.           0.           0.          23.          -1.04358761] tensor(4859.0713)\n",
      "[  1.        407.          1.          1.         42.         86.\n",
      "   0.          0.          0.          0.          0.          0.\n",
      "   0.         31.          0.6412624] tensor(8297.9980)\n",
      "[ 3.00000000e+00  1.70300000e+03  0.00000000e+00  0.00000000e+00\n",
      "  4.20000000e+01  8.60000000e+01  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  3.30000000e+01 -5.11043371e-01] tensor(5902.6431)\n",
      "[  3.         734.           1.           1.          35.\n",
      " 115.           1.           0.           0.           0.\n",
      "   0.           0.           0.          22.          -1.39501774] tensor(4000.)\n",
      "[  1.         652.           0.           1.          37.\n",
      " 112.           0.           2.           0.           0.\n",
      "   0.           0.           0.          31.          -1.29818526] tensor(4268.)\n",
      "[  1.         714.           0.           1.          29.\n",
      " 113.           0.           2.           0.           0.\n",
      "   0.           0.           0.          33.           1.86966682] tensor(16005.)\n",
      "[ 2.00000000e+00  1.70300000e+03  0.00000000e+00  0.00000000e+00\n",
      "  2.80000000e+01  1.13000000e+02  1.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  3.00000000e+01 -1.18132525e+00] tensor(4553.9561)\n",
      "[ 1.00000000e+00  1.70300000e+03  0.00000000e+00  0.00000000e+00\n",
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      "[  1.         658.           0.           1.          41.\n",
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      "  0.00000000e+00  3.30000000e+01 -4.59278471e-01] tensor(6000.)\n",
      "[  2.         840.           0.           1.          42.\n",
      "  86.           0.           0.           0.           0.\n",
      "   0.           0.           0.          33.           1.20889385] tensor(10080.1406)\n",
      "[ 2.00000000e+00  7.34000000e+02  1.00000000e+00  1.00000000e+00\n",
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      "  0.00000000e+00  9.00000000e+00 -7.06774568e-01] tensor(5531.9990)\n",
      "[1.00000000e+00 1.56000000e+02 0.00000000e+00 0.00000000e+00\n",
      " 3.70000000e+01 1.12000000e+02 0.00000000e+00 2.00000000e+00\n",
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      " 0.00000000e+00 3.30000000e+01 1.43569229e-01] tensor(7170.3403)\n",
      "[ 1.          9.          0.          1.         42.         86.\n",
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      "  0.         33.          0.73256683] tensor(8536.)\n",
      "[  1.         719.           0.           1.          41.\n",
      " 123.           0.           2.           0.           0.\n",
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      "[ 12.         161.           0.           1.          31.\n",
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      "   0.           0.           0.          33.           1.20889385] tensor(10080.1406)\n",
      "[ 2.00000000e+00  7.34000000e+02  1.00000000e+00  1.00000000e+00\n",
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      "  0.00000000e+00  3.30000000e+01 -5.11043371e-01] tensor(5902.6431)\n",
      "[  3.         424.           0.           1.          42.\n",
      "  86.           0.           0.           0.           0.\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "   0.           0.           0.          33.          -1.04358761] tensor(4859.0713)\n",
      "[  2.         160.           1.           1.          34.\n",
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      "[  2.         159.           1.           1.          30.\n",
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      "[  2.        840.          0.          1.         42.         86.\n",
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      "[  2.         748.           0.           1.          23.\n",
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      "[  1.         554.           1.           1.          28.\n",
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      "[  2.         160.           1.           1.          22.\n",
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      "[  2.         167.           0.           1.          36.\n",
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      "[  1.         874.           0.           1.          42.\n",
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      "[  3.         311.           0.           1.          42.\n",
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      "[  2.         652.           0.           1.          23.\n",
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      "[  1.         734.           1.           1.          36.\n",
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      "[  1.           9.           0.           1.          39.\n",
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      "[  2.         748.           0.           1.          45.\n",
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      "  0.00000000e+00  3.30000000e+01 -2.46441106e-01] tensor(6402.)\n",
      "[  2.         839.           0.           1.          37.\n",
      " 114.           1.           0.           0.           0.\n",
      "   0.           0.           0.          33.          -1.39501774] tensor(4000.)\n",
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      " 0.00000000e+00 2.90000000e+01 4.24233531e-01] tensor(7776.9434)\n",
      "[  1.        753.          0.          1.         23.        113.\n",
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      " 0.00000000e+00 3.00000000e+01 1.43569229e-01] tensor(7170.3403)\n",
      "[ 12.        407.          1.          1.         42.         86.\n",
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      "[  1.         635.           0.           1.          32.\n",
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      "[  1.        554.          1.          1.         39.        116.\n",
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      "[  2.          54.           0.           1.          38.\n",
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      "[  2.         159.           1.           1.          34.\n",
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      "[ 2.00000000e+00  8.70000000e+02  0.00000000e+00  1.00000000e+00\n",
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      "[3.00000000e+00 5.54000000e+02 1.00000000e+00 1.00000000e+00\n",
      " 3.40000000e+01 1.15000000e+02 1.00000000e+00 0.00000000e+00\n",
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      " 0.00000000e+00 3.30000000e+01 2.00470543e-01] tensor(7288.6064)\n",
      "[1.00000000e+00 1.70300000e+03 0.00000000e+00 0.00000000e+00\n",
      " 2.30000000e+01 1.14000000e+02 0.00000000e+00 2.00000000e+00\n",
      " 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00\n",
      " 0.00000000e+00 3.00000000e+01 1.18880493e+00] tensor(10000.)\n",
      "[  1.         348.           0.           1.          30.\n",
      " 103.           0.           2.           3.           3.\n",
      "   0.           0.           3.          27.           1.20889385] tensor(10080.1406)\n",
      "[ 1.00000000e+00  7.36000000e+02  0.00000000e+00  1.00000000e+00\n",
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      "  0.00000000e+00  2.90000000e+01 -2.46441106e-01] tensor(6402.)\n",
      "[ 2.00000000e+00  7.47000000e+02  0.00000000e+00  1.00000000e+00\n",
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      "[  1.          10.           0.           1.          40.\n",
      " 114.           0.           2.           0.           0.\n",
      "   0.           0.           0.          31.           0.51998844] tensor(8000.)\n",
      "[  1.         162.           0.           1.          39.\n",
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      "[ 2.00000000e+00  8.52000000e+02  0.00000000e+00  1.00000000e+00\n",
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      "  0.00000000e+00  3.30000000e+01 -2.46441106e-01] tensor(6402.)\n",
      "[  1.         615.           0.           0.          31.\n",
      " 117.           0.           2.           0.           0.\n",
      "   0.           0.           0.          20.          -1.29818526] tensor(4268.)\n",
      "[1.00000000e+00 9.44000000e+02 0.00000000e+00 1.00000000e+00\n",
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      " 0.00000000e+00 2.90000000e+01 8.46845955e-01] tensor(8853.9639)\n",
      "[  1.         749.           0.           1.          37.\n",
      " 117.           0.           2.           0.           0.\n",
      "   0.           0.           0.          31.           1.34300582] tensor(10670.)\n",
      "[ 12.         311.           0.           1.          39.\n",
      " 116.           0.           2.           3.           3.\n",
      "   0.           0.           0.          33.           1.18880493] tensor(10000.)\n",
      "[3.00000000e+00 1.70300000e+03 0.00000000e+00 0.00000000e+00\n",
      " 4.20000000e+01 8.60000000e+01 0.00000000e+00 0.00000000e+00\n",
      " 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00\n",
      " 0.00000000e+00 3.30000000e+01 8.46845955e-01] tensor(8853.9639)\n",
      "[  2.         652.           0.           1.          36.\n",
      " 117.           1.           0.           0.           0.\n",
      "   0.           0.           0.          31.          -1.04358761] tensor(4859.0713)\n",
      "[ 1.00000000e+00  6.52000000e+02  0.00000000e+00  1.00000000e+00\n",
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      "  0.00000000e+00  2.40000000e+01 -4.59278471e-01] tensor(6000.)\n",
      "[  1.         373.           0.           1.          41.\n",
      " 122.           0.           2.           0.           0.\n",
      "   0.           0.           0.          24.          -0.51104337] tensor(5902.6431)\n",
      "[  1.         714.           0.           1.          24.\n",
      " 118.           0.           2.           0.           0.\n",
      "   0.           0.           0.          33.          -0.88503262] tensor(5184.6289)\n",
      "[  1.         289.           0.           1.          38.\n",
      " 121.           0.           2.           0.           0.\n",
      "   0.           0.           0.          23.           0.73256683] tensor(8536.)\n",
      "[2.00000000e+00 7.48000000e+02 0.00000000e+00 1.00000000e+00\n",
      " 4.60000000e+01 1.24000000e+02 0.00000000e+00 2.00000000e+00\n",
      " 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00\n",
      " 0.00000000e+00 3.30000000e+01 3.68223674e-01] tensor(7650.7529)\n",
      "[2.00000000e+00 1.70300000e+03 0.00000000e+00 0.00000000e+00\n",
      " 3.90000000e+01 1.16000000e+02 1.00000000e+00 0.00000000e+00\n",
      " 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00\n",
      " 0.00000000e+00 3.10000000e+01 1.43569229e-01] tensor(7170.3403)\n",
      "[  2.         411.           0.           1.          37.\n",
      " 114.           1.           0.           0.           0.\n",
      "   0.           0.           0.          31.           0.42423353] tensor(7776.9434)\n",
      "[  1.         841.           0.           1.          34.\n",
      " 113.           0.           2.           0.           0.\n",
      "   0.           0.           0.          33.          -1.04358761] tensor(4859.0713)\n",
      "[ 1.00000000e+00  3.48000000e+02  0.00000000e+00  1.00000000e+00\n",
      "  3.80000000e+01  1.15000000e+02  0.00000000e+00  2.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  3.10000000e+01 -3.01143857e-01] tensor(6298.1201)\n",
      "[  1.         635.           0.           1.          42.\n",
      "  86.           0.           0.           0.           0.\n",
      "   0.           0.           0.          33.          -0.88503262] tensor(5184.6289)\n",
      "[  3.         852.           0.           1.          35.\n",
      " 119.           1.           0.           0.           0.\n",
      "   0.           0.           0.          33.          -1.39501774] tensor(4000.)\n",
      "[  1.         840.           0.           1.          45.\n",
      " 126.           0.           2.           0.           0.\n",
      "   0.           0.           0.          15.           1.86015571] tensor(15745.2998)\n",
      "[  2.         652.           0.           1.          42.\n",
      "  86.           0.           0.           0.           0.\n",
      "   0.           0.           0.          30.           1.11436842] tensor(9718.1426)\n",
      "[  1.         749.           0.           1.          31.\n",
      " 117.           0.           2.           0.           0.\n",
      "   0.           0.           0.          33.          -1.29818526] tensor(4268.)\n",
      "[ 1.00000000e+00  1.70300000e+03  0.00000000e+00  0.00000000e+00\n",
      "  2.20000000e+01  1.13000000e+02  0.00000000e+00  2.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  3.30000000e+01 -2.46441106e-01] tensor(6402.)\n",
      "[  2.         151.           0.           1.          31.\n",
      " 121.           0.           2.           0.           0.\n",
      "   0.           0.           0.          29.           0.51998844] tensor(8000.)\n",
      "[ 1.00000000e+00  9.44000000e+02  0.00000000e+00  1.00000000e+00\n",
      "  3.10000000e+01  1.17000000e+02  0.00000000e+00  2.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  2.90000000e+01 -3.01143857e-01] tensor(6298.1201)\n",
      "[  1.         734.           1.           1.          22.\n",
      " 113.           0.           2.           0.           0.\n",
      "   0.           0.           0.          30.          -1.18132525] tensor(4553.9561)\n",
      "[  1.         257.           1.           1.          23.\n",
      " 113.           0.           2.           0.           0.\n",
      "   0.           0.           0.          30.          -1.18132525] tensor(4553.9561)\n",
      "[ 2.00000000e+00  8.70000000e+02  0.00000000e+00  1.00000000e+00\n",
      "  3.40000000e+01  1.13000000e+02  0.00000000e+00  2.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  2.80000000e+01 -2.46441106e-01] tensor(6402.)\n",
      "[ 1.00000000e+00  7.34000000e+02  1.00000000e+00  1.00000000e+00\n",
      "  2.90000000e+01  1.04000000e+02  0.00000000e+00  2.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  3.30000000e+01 -2.48496109e-02] tensor(6830.9341)\n",
      "[2.00000000e+00 1.64300000e+03 0.00000000e+00 1.00000000e+00\n",
      " 3.90000000e+01 1.16000000e+02 0.00000000e+00 2.00000000e+00\n",
      " 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00\n",
      " 0.00000000e+00 3.30000000e+01 4.24233531e-01] tensor(7776.9434)\n",
      "[  2.         410.           0.           1.          39.\n",
      " 116.           0.           2.           0.           0.\n",
      "   0.           0.           0.          31.          -1.18132525] tensor(4553.9561)\n",
      "[ 11.         871.           0.           1.          42.\n",
      "  86.           0.           0.           0.           0.\n",
      "   0.           0.           0.          33.           1.03704191] tensor(9447.1797)\n",
      "[  1.         407.           1.           1.          40.\n",
      " 114.           0.           2.           0.           0.\n",
      "   0.           0.           0.          33.           1.58881165] tensor(12147.6777)\n",
      "[  2.        635.          0.          1.         34.        108.\n",
      "   0.          2.          0.          0.          0.          0.\n",
      "   0.         33.          0.6412624] tensor(8297.9980)\n",
      "[1.00000000e+00 9.44000000e+02 0.00000000e+00 1.00000000e+00\n",
      " 4.20000000e+01 8.60000000e+01 0.00000000e+00 0.00000000e+00\n",
      " 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00\n",
      " 0.00000000e+00 3.10000000e+01 8.46845955e-01] tensor(8853.9639)\n",
      "[1.00000000e+00 6.52000000e+02 0.00000000e+00 1.00000000e+00\n",
      " 2.40000000e+01 1.18000000e+02 0.00000000e+00 2.00000000e+00\n",
      " 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00\n",
      " 0.00000000e+00 2.10000000e+01 2.00470543e-01] tensor(7288.6064)\n",
      "[ 1.00000000e+00  1.70300000e+03  0.00000000e+00  0.00000000e+00\n",
      "  3.80000000e+01  1.14000000e+02  0.00000000e+00  2.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  3.10000000e+01 -1.04358761e+00] tensor(4859.0713)\n",
      "[  1.         811.           0.           0.          34.\n",
      " 113.           0.           2.           0.           0.\n",
      "   0.           0.           0.          33.          -1.39501774] tensor(4000.)\n",
      "[  1.         734.           1.           1.          26.\n",
      " 112.           0.           2.           0.           0.\n",
      "   0.           0.           0.          30.          -1.29818526] tensor(4268.)\n",
      "[1.00000000e+00 8.42000000e+02 0.00000000e+00 1.00000000e+00\n",
      " 3.90000000e+01 1.16000000e+02 0.00000000e+00 2.00000000e+00\n",
      " 3.00000000e+00 3.00000000e+00 0.00000000e+00 0.00000000e+00\n",
      " 0.00000000e+00 3.10000000e+01 4.24233531e-01] tensor(7776.9434)\n",
      "[ 2.00000000e+00  8.45000000e+02  0.00000000e+00  0.00000000e+00\n",
      "  2.20000000e+01  1.13000000e+02  1.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  3.00000000e+01 -2.48496109e-02] tensor(6830.9341)\n",
      "[2.00000000e+00 8.40000000e+02 0.00000000e+00 1.00000000e+00\n",
      " 4.30000000e+01 1.25000000e+02 0.00000000e+00 2.00000000e+00\n",
      " 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00\n",
      " 0.00000000e+00 3.30000000e+01 6.41262404e-01] tensor(8297.9980)\n",
      "[ 3.00000000e+00  1.70300000e+03  0.00000000e+00  0.00000000e+00\n",
      "  4.20000000e+01  8.60000000e+01  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  3.30000000e+01 -1.04358761e+00] tensor(4859.0713)\n",
      "[  2.         852.           0.           1.          22.\n",
      " 113.           1.           0.           0.           0.\n",
      "   0.           0.           0.          30.          -1.39501774] tensor(4000.)\n",
      "[ 1.00000000e+00  7.49000000e+02  0.00000000e+00  1.00000000e+00\n",
      "  3.60000000e+01  1.00000000e+02  0.00000000e+00  2.00000000e+00\n",
      "  3.00000000e+00  3.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  2.10000000e+01 -4.59278471e-01] tensor(6000.)\n",
      "[ 2.00000000e+00  1.42900000e+03  0.00000000e+00  1.00000000e+00\n",
      "  3.40000000e+01  1.08000000e+02  1.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  3.30000000e+01 -2.46441106e-01] tensor(6402.)\n",
      "[ 2.        54.         0.         1.        42.        86.\n",
      "  0.         0.         0.         0.         0.         0.\n",
      "  0.        27.         0.6412624] tensor(8297.9980)\n",
      "[  1.         230.           0.           1.          25.\n",
      " 119.           0.           2.           0.           0.\n",
      "   0.           0.           0.          21.          -1.29818526] tensor(4268.)\n",
      "[  1.           9.           0.           1.          40.\n",
      " 116.           0.           2.           3.           3.\n",
      "   0.           0.           0.          21.          -0.24644111] tensor(6402.)\n",
      "[  8.         407.           1.           1.          28.\n",
      " 115.           0.           2.           0.           0.\n",
      "   0.           0.           0.          30.           1.20889385] tensor(10080.1406)\n",
      "[2.00000000e+00 1.70300000e+03 0.00000000e+00 0.00000000e+00\n",
      " 4.20000000e+01 8.60000000e+01 0.00000000e+00 0.00000000e+00\n",
      " 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00\n",
      " 0.00000000e+00 3.30000000e+01 1.43569229e-01] tensor(7170.3403)\n",
      "[  1.         753.           0.           1.          38.\n",
      " 115.           0.           2.           0.           0.\n",
      "   0.           0.           0.          33.           0.93187116] tensor(9107.9121)\n",
      "[  1.         652.           0.           1.          30.\n",
      " 120.           0.           2.           3.           3.\n",
      "   4.           0.           3.          33.           1.36054634] tensor(10755.5107)\n",
      "[  1.         151.           0.           1.          30.\n",
      " 114.           0.           2.           3.           3.\n",
      "   0.           0.           3.          30.           1.89750278] tensor(16934.8730)\n",
      "[  1.         635.           0.           1.          34.\n",
      " 108.           0.           2.           0.           0.\n",
      "   0.           0.           0.          33.           0.84684595] tensor(8853.9639)\n",
      "[  1.         160.           1.           1.          42.\n",
      "  86.           0.           0.           0.           0.\n",
      "   0.           0.           0.          33.          -1.29818526] tensor(4268.)\n",
      "[ 2.00000000e+00  1.70300000e+03  0.00000000e+00  0.00000000e+00\n",
      "  4.20000000e+01  8.60000000e+01  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  3.10000000e+01 -2.46441106e-01] tensor(6402.)\n",
      "[ 1.00000000e+00  6.52000000e+02  0.00000000e+00  1.00000000e+00\n",
      "  4.20000000e+01  8.60000000e+01  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  2.00000000e+01 -5.11043371e-01] tensor(5902.6431)\n",
      "[  2.        748.          0.          1.         29.        106.\n",
      "   1.          0.          0.          0.          0.          0.\n",
      "   0.         33.          1.2775747] tensor(10369.2578)\n",
      "[2.00000000e+00 1.70300000e+03 0.00000000e+00 0.00000000e+00\n",
      " 4.20000000e+01 8.60000000e+01 0.00000000e+00 0.00000000e+00\n",
      " 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00\n",
      " 0.00000000e+00 2.50000000e+01 3.68223674e-01] tensor(7650.7529)\n",
      "[  1.         714.           0.           1.          43.\n",
      " 125.           0.           2.           0.           0.\n",
      "   0.           0.           0.          31.          -0.88503262] tensor(5184.6289)\n",
      "[2.00000000e+00 8.44000000e+02 0.00000000e+00 1.00000000e+00\n",
      " 4.00000000e+01 1.24000000e+02 0.00000000e+00 2.00000000e+00\n",
      " 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00\n",
      " 0.00000000e+00 3.10000000e+01 1.43569229e-01] tensor(7170.3403)\n",
      "[2.00000000e+00 8.52000000e+02 0.00000000e+00 1.00000000e+00\n",
      " 4.20000000e+01 8.60000000e+01 0.00000000e+00 0.00000000e+00\n",
      " 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00\n",
      " 0.00000000e+00 3.00000000e+01 2.00470543e-01] tensor(7288.6064)\n",
      "[  1.         230.           0.           1.          42.\n",
      "  86.           0.           0.           0.           0.\n",
      "   0.           0.           0.          33.           0.93187116] tensor(9107.9121)\n",
      "[  1.         159.           1.           1.          42.\n",
      "  86.           0.           0.           0.           0.\n",
      "   0.           0.           0.          33.          -0.51104337] tensor(5902.6431)\n",
      "[  1.         162.           0.           1.          43.\n",
      " 126.           0.           2.           0.           0.\n",
      "   0.           0.           0.          33.          -1.04358761] tensor(4859.0713)\n",
      "[2.00000000e+00 4.10000000e+02 0.00000000e+00 1.00000000e+00\n",
      " 2.20000000e+01 1.13000000e+02 1.00000000e+00 0.00000000e+00\n",
      " 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00\n",
      " 0.00000000e+00 3.00000000e+01 2.00470543e-01] tensor(7288.6064)\n",
      "[ 2.00000000e+00  1.70300000e+03  0.00000000e+00  0.00000000e+00\n",
      "  4.10000000e+01  1.23000000e+02  0.00000000e+00  2.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  2.40000000e+01 -2.48496109e-02] tensor(6830.9341)\n",
      "[1.00000000e+00 4.07000000e+02 1.00000000e+00 1.00000000e+00\n",
      " 3.10000000e+01 1.21000000e+02 0.00000000e+00 2.00000000e+00\n",
      " 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00\n",
      " 0.00000000e+00 3.30000000e+01 3.68223674e-01] tensor(7650.7529)\n",
      "[ 2.00000000e+00  4.07000000e+02  1.00000000e+00  1.00000000e+00\n",
      "  3.00000000e+01  1.12000000e+02  1.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  2.50000000e+01 -2.48496109e-02] tensor(6830.9341)\n",
      "[  2.        554.          1.          1.         29.        105.\n",
      "   1.          0.          0.          0.          0.          0.\n",
      "   0.         31.          1.9010312] tensor(17077.3359)\n",
      "[ 1.00000000e+00  8.42000000e+02  0.00000000e+00  1.00000000e+00\n",
      "  4.20000000e+01  8.60000000e+01  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  3.10000000e+01 -2.48496109e-02] tensor(6830.9341)\n",
      "[ 2.00000000e+00  1.42900000e+03  0.00000000e+00  1.00000000e+00\n",
      "  3.40000000e+01  1.13000000e+02  1.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  3.30000000e+01 -5.11043371e-01] tensor(5902.6431)\n",
      "[1.00000000e+00 7.41000000e+02 0.00000000e+00 1.00000000e+00\n",
      " 2.80000000e+01 1.12000000e+02 0.00000000e+00 2.00000000e+00\n",
      " 3.00000000e+00 3.00000000e+00 0.00000000e+00 0.00000000e+00\n",
      " 3.00000000e+00 3.30000000e+01 4.24233531e-01] tensor(7776.9434)\n",
      "[4.00000000e+00 1.70300000e+03 0.00000000e+00 0.00000000e+00\n",
      " 4.20000000e+01 8.60000000e+01 0.00000000e+00 0.00000000e+00\n",
      " 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00\n",
      " 0.00000000e+00 3.10000000e+01 5.87419996e-01] tensor(8163.3535)\n",
      "[  1.         771.           0.           1.          36.\n",
      " 103.           0.           2.           0.           0.\n",
      "   0.           0.           0.          10.          -1.18132525] tensor(4553.9561)\n",
      "[ 2.00000000e+00  9.44000000e+02  0.00000000e+00  1.00000000e+00\n",
      "  4.20000000e+01  8.60000000e+01  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  3.10000000e+01 -8.13051736e-02] tensor(6720.0938)\n",
      "[  2.         159.           1.           1.          31.\n",
      " 118.           1.           0.           0.           0.\n",
      "   0.           0.           0.          33.           0.42423353] tensor(7776.9434)\n",
      "[  1.         162.           0.           1.          39.\n",
      " 116.           0.           2.           0.           0.\n",
      "   0.           0.           0.          31.           1.95140677] tensor(20744.9961)\n",
      "[  2.         162.           0.           1.          31.\n",
      " 121.           1.           0.           0.           0.\n",
      "   0.           0.           0.          29.          -0.51104337] tensor(5902.6431)\n",
      "[  1.         734.           1.           1.          31.\n",
      " 112.           0.           2.           0.           0.\n",
      "   0.           0.           0.          31.          -1.39501774] tensor(4000.)\n",
      "[  1.         875.           0.           0.          32.\n",
      " 112.           0.           2.           0.           0.\n",
      "   0.           0.           0.          18.          -1.29818526] tensor(4268.)\n",
      "[1.00000000e+00 8.69000000e+02 0.00000000e+00 1.00000000e+00\n",
      " 3.00000000e+01 1.03000000e+02 0.00000000e+00 2.00000000e+00\n",
      " 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00\n",
      " 0.00000000e+00 3.10000000e+01 4.24233531e-01] tensor(7776.9434)\n",
      "[  2.         554.           1.           1.          32.\n",
      " 120.           1.           0.           0.           0.\n",
      "   0.           0.           0.          33.           1.81503227] tensor(14756.6074)\n",
      "[ 2.00000000e+00  8.56000000e+02  0.00000000e+00  1.00000000e+00\n",
      "  3.00000000e+01  1.20000000e+02  0.00000000e+00  2.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  2.80000000e+01 -7.06774568e-01] tensor(5531.9990)\n",
      "[ 1.00000000e+00  2.57000000e+02  1.00000000e+00  1.00000000e+00\n",
      "  3.70000000e+01  1.14000000e+02  0.00000000e+00  2.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  3.30000000e+01 -2.48496109e-02] tensor(6830.9341)\n",
      "[ 1.00000000e+00  1.70300000e+03  0.00000000e+00  0.00000000e+00\n",
      "  4.30000000e+01  8.70000000e+01  0.00000000e+00  2.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  3.00000000e+01 -2.46441106e-01] tensor(6402.)\n",
      "[  2.         851.           0.           1.          31.\n",
      " 120.           1.           0.           0.           0.\n",
      "   0.           0.           0.          26.          -0.88503262] tensor(5184.6289)\n",
      "[ 12.         363.           0.           1.          34.\n",
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      "   0.           0.           0.          33.           1.03704191] tensor(9447.1797)\n",
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      " 3.00000000e+00 3.00000000e+01 7.32566829e-01] tensor(8536.)\n",
      "[ 2.00000000e+00  1.70300000e+03  0.00000000e+00  0.00000000e+00\n",
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      "  0.00000000e+00  3.30000000e+01 -5.11043371e-01] tensor(5902.6431)\n",
      "[ 2.00000000e+00  1.70300000e+03  0.00000000e+00  0.00000000e+00\n",
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      "  0.00000000e+00  1.60000000e+01 -4.59278471e-01] tensor(6000.)\n",
      "[ 2.00000000e+00  7.47000000e+02  0.00000000e+00  1.00000000e+00\n",
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      "[  1.         348.           0.           1.          34.\n",
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      "[  1.         310.           0.           1.          31.\n",
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      "[  1.         362.           0.           1.          34.\n",
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      "[  1.         749.           0.           1.          39.\n",
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      "   0.           0.           0.          19.           0.93187116] tensor(9107.9121)\n",
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      "  0.00000000e+00  2.60000000e+01 -2.48496109e-02] tensor(6830.9341)\n",
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      " 0.00000000e+00 3.00000000e+01 2.00470543e-01] tensor(7288.6064)\n",
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      " 0.00000000e+00 3.30000000e+01 3.68223674e-01] tensor(7650.7529)\n",
      "[  2.         851.           0.           1.          23.\n",
      " 113.           1.           0.           0.           0.\n",
      "   0.           0.           0.          31.           0.93187116] tensor(9107.9121)\n",
      "[ 2.00000000e+00  1.70300000e+03  0.00000000e+00  0.00000000e+00\n",
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      "  0.00000000e+00  2.30000000e+01 -1.18132525e+00] tensor(4553.9561)\n",
      "[  1.         407.           1.           1.          41.\n",
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      "[  2.         944.           0.           1.          32.\n",
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      " 0.00000000e+00 3.30000000e+01 6.41262404e-01] tensor(8297.9980)\n",
      "[1.0000000e+00 8.4100000e+02 0.0000000e+00 1.0000000e+00 4.5000000e+01\n",
      " 1.2600000e+02 0.0000000e+00 2.0000000e+00 0.0000000e+00 0.0000000e+00\n",
      " 0.0000000e+00 0.0000000e+00 0.0000000e+00 3.3000000e+01 5.1998844e-01] tensor(8000.)\n",
      "[  2.        200.          0.          1.         42.         86.\n",
      "   0.          0.          0.          0.          0.          0.\n",
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      "[  1.         407.           1.           1.          39.\n",
      " 117.           0.           2.           3.           0.\n",
      "   0.           0.           0.          31.           1.34300582] tensor(10670.)\n",
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      " 0.00000000e+00 2.30000000e+01 1.43569229e-01] tensor(7170.3403)\n",
      "[  1.         734.           1.           1.          31.\n",
      " 118.           0.           2.           3.           3.\n",
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      "[  1.         842.           0.           1.          39.\n",
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      "[  2.          54.           0.           1.          28.\n",
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      "   0.           0.           0.          30.          -0.51104337] tensor(5902.6431)\n",
      "[3.00000000e+00 7.47000000e+02 0.00000000e+00 1.00000000e+00\n",
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      " 0.00000000e+00 3.30000000e+01 7.32566829e-01] tensor(8536.)\n",
      "[ 2.00000000e+00  1.70300000e+03  0.00000000e+00  0.00000000e+00\n",
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      "  0.00000000e+00  3.30000000e+01 -7.06774568e-01] tensor(5531.9990)\n",
      "[  1.         160.           1.           1.          40.\n",
      " 111.           0.           2.           0.           0.\n",
      "   0.           0.           0.          31.          -1.39501774] tensor(4000.)\n",
      "[ 1.00000000e+00  7.34000000e+02  1.00000000e+00  1.00000000e+00\n",
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      "  0.00000000e+00  3.30000000e+01 -4.59278471e-01] tensor(6000.)\n",
      "[  1.         754.           0.           1.          30.\n",
      " 103.           0.           2.           3.           3.\n",
      "   0.           0.           3.          31.          -0.88503262] tensor(5184.6289)\n",
      "[ 1.20000000e+01  7.53000000e+02  0.00000000e+00  1.00000000e+00\n",
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      "  0.00000000e+00  2.50000000e+01 -3.01143857e-01] tensor(6298.1201)\n",
      "[ 12.         652.           0.           1.          34.\n",
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      "[  1.         348.           0.           1.          30.\n",
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      "[  2.         754.           0.           1.          23.\n",
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      "[  1.         407.           1.           1.          38.\n",
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      "[ 2.         83.          0.          1.         42.         86.\n",
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      "[  2.         162.           0.           1.          31.\n",
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      "[ 2.00000000e+00  1.70300000e+03  0.00000000e+00  0.00000000e+00\n",
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      "[  1.         629.           0.           1.          26.\n",
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      "[  2.         853.           0.           1.          34.\n",
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      "[  1.         162.           0.           1.          32.\n",
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      "[  1.         944.           0.           1.          30.\n",
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      "[  3.         160.           1.           1.          42.\n",
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      "[1.00000000e+00 1.70300000e+03 0.00000000e+00 0.00000000e+00\n",
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      " 0.00000000e+00 3.30000000e+01 3.68223674e-01] tensor(7650.7529)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[ 2.00000000e+00  7.34000000e+02  1.00000000e+00  1.00000000e+00\n",
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      "[  1.         416.           0.           1.          29.\n",
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      "[   7.         1703.            0.            0.           42.\n",
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      "[  1.         635.           0.           1.          30.\n",
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      "[  1.         159.           1.           1.          30.\n",
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      "[  1.         260.           0.           1.          30.\n",
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      "[ 3.00000000e+00  1.70300000e+03  0.00000000e+00  0.00000000e+00\n",
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      "[  2.         635.           0.           1.          23.\n",
      " 113.           1.           0.           0.           0.\n",
      "   0.           0.           0.          30.           1.34300582] tensor(10670.)\n",
      "[  1.         554.           1.           1.          46.\n",
      " 125.           0.           2.           0.           0.\n",
      "   0.           0.           0.          33.          -0.70677457] tensor(5531.9990)\n",
      "[  1.         841.           0.           1.          34.\n",
      " 109.           0.           2.           0.           0.\n",
      "   0.           0.           0.          33.          -1.18132525] tensor(4553.9561)\n",
      "[2.00000000e+00 1.19900000e+03 0.00000000e+00 1.00000000e+00\n",
      " 4.00000000e+01 1.22000000e+02 1.00000000e+00 0.00000000e+00\n",
      " 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00\n",
      " 0.00000000e+00 2.40000000e+01 7.32566829e-01] tensor(8536.)\n",
      "[2.0000000e+00 7.4700000e+02 0.0000000e+00 1.0000000e+00 3.2000000e+01\n",
      " 1.1800000e+02 1.0000000e+00 0.0000000e+00 0.0000000e+00 0.0000000e+00\n",
      " 0.0000000e+00 0.0000000e+00 0.0000000e+00 3.1000000e+01 5.1998844e-01] tensor(8000.)\n",
      "[ 1.00000000e+00  9.44000000e+02  0.00000000e+00  1.00000000e+00\n",
      "  2.50000000e+01  1.13000000e+02  0.00000000e+00  2.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  1.70000000e+01 -2.46441106e-01] tensor(6402.)\n",
      "[  2.         840.           0.           1.          36.\n",
      " 120.           0.           2.           0.           0.\n",
      "   0.           0.           0.          33.           1.92387304] tensor(18221.5156)\n",
      "[ 2.00000000e+00  7.34000000e+02  1.00000000e+00  1.00000000e+00\n",
      "  4.20000000e+01  8.60000000e+01  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  3.10000000e+01 -2.46441106e-01] tensor(6402.)\n",
      "[ 2.00000000e+00  1.24500000e+03  0.00000000e+00  1.00000000e+00\n",
      "  2.10000000e+01  1.11000000e+02  1.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  3.00000000e+01 -8.85032618e-01] tensor(5184.6289)\n",
      "[ 1.00000000e+00  4.07000000e+02  1.00000000e+00  1.00000000e+00\n",
      "  2.50000000e+01  1.10000000e+02  0.00000000e+00  2.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  3.30000000e+01 -2.48496109e-02] tensor(6830.9341)\n",
      "[  1.           9.           0.           1.          34.\n",
      " 108.           0.           2.           0.           0.\n",
      "   0.           0.           0.          33.           1.58881165] tensor(12147.6777)\n",
      "[1.10000000e+01 1.70300000e+03 0.00000000e+00 0.00000000e+00\n",
      " 4.20000000e+01 8.60000000e+01 0.00000000e+00 0.00000000e+00\n",
      " 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00\n",
      " 0.00000000e+00 3.10000000e+01 4.24233531e-01] tensor(7776.9434)\n",
      "[ 2.00000000e+00  1.24500000e+03  0.00000000e+00  1.00000000e+00\n",
      "  3.30000000e+01  1.07000000e+02  1.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  3.30000000e+01 -8.85032618e-01] tensor(5184.6289)\n",
      "[  2.         635.           0.           1.          42.\n",
      "  86.           0.           0.           0.           0.\n",
      "   0.           0.           0.          30.           1.36054634] tensor(10755.5107)\n",
      "[  2.         162.           0.           1.          33.\n",
      " 119.           1.           0.           0.           0.\n",
      "   0.           0.           0.          26.          -0.88503262] tensor(5184.6289)\n",
      "[ 12.        407.          1.          1.         36.        120.\n",
      "   0.          2.          0.          0.          0.          0.\n",
      "   0.         33.          0.6412624] tensor(8297.9980)\n",
      "[  2.        178.          0.          1.         42.         86.\n",
      "   0.          0.          0.          0.          0.          0.\n",
      "   0.         29.          0.6412624] tensor(8297.9980)\n",
      "[  1.          57.           0.           1.          41.\n",
      " 123.           0.           2.           0.           0.\n",
      "   0.           0.           0.          31.          -1.29818526] tensor(4268.)\n",
      "[  2.         652.           0.           1.          42.\n",
      "  86.           0.           0.           0.           0.\n",
      "   0.           0.           0.          30.           1.58881165] tensor(12147.6777)\n",
      "[  1.         719.           0.           1.          29.\n",
      " 105.           0.           2.           0.           0.\n",
      "   0.           0.           0.          30.          -0.88503262] tensor(5184.6289)\n",
      "[  1.         851.           0.           1.          38.\n",
      " 121.           0.           2.           0.           0.\n",
      "   0.           0.           0.          24.          -1.18132525] tensor(4553.9561)\n",
      "[  1.        407.          1.          1.         29.        106.\n",
      "   0.          2.          0.          0.          0.          0.\n",
      "   0.         33.         -1.1192525] tensor(4694.7998)\n",
      "[  2.         159.           1.           1.          22.\n",
      " 113.           0.           2.           0.           0.\n",
      "   0.           0.           0.          30.          -0.88503262] tensor(5184.6289)\n",
      "[  2.         269.           0.           1.          39.\n",
      " 117.           1.           0.           0.           0.\n",
      "   0.           0.           0.          31.          -1.04358761] tensor(4859.0713)\n",
      "[  1.         847.           0.           1.          27.\n",
      " 106.           0.           2.           0.           0.\n",
      "   0.           0.           0.          33.           1.91880381] tensor(17925.8516)\n",
      "[ 2.00000000e+00  8.40000000e+02  0.00000000e+00  1.00000000e+00\n",
      "  4.20000000e+01  8.60000000e+01  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  3.10000000e+01 -7.06774568e-01] tensor(5531.9990)\n",
      "[2.00000000e+00 7.47000000e+02 0.00000000e+00 1.00000000e+00\n",
      " 3.80000000e+01 1.17000000e+02 1.00000000e+00 0.00000000e+00\n",
      " 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00\n",
      " 0.00000000e+00 3.10000000e+01 2.00470543e-01] tensor(7288.6064)\n",
      "[  1.         554.           1.           1.          34.\n",
      " 108.           0.           2.           0.           0.\n",
      "   0.           0.           0.          33.           1.95140677] tensor(20744.9961)\n",
      "[  1.         159.           1.           1.          31.\n",
      " 117.           0.           2.           3.           3.\n",
      "   4.           0.           3.          20.          -0.24644111] tensor(6402.)\n",
      "[  2.         754.           0.           1.          39.\n",
      " 117.           1.           0.           0.           0.\n",
      "   0.           0.           0.          31.           0.84684595] tensor(8853.9639)\n",
      "[ 2.00000000e+00  1.70300000e+03  0.00000000e+00  0.00000000e+00\n",
      "  2.80000000e+01  1.13000000e+02  1.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  3.30000000e+01 -1.18132525e+00] tensor(4553.9561)\n",
      "[1.00000000e+00 7.34000000e+02 1.00000000e+00 1.00000000e+00\n",
      " 3.60000000e+01 1.16000000e+02 0.00000000e+00 2.00000000e+00\n",
      " 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00\n",
      " 0.00000000e+00 3.30000000e+01 2.00470543e-01] tensor(7288.6064)\n",
      "[  1.         635.           0.           1.          30.\n",
      " 114.           0.           2.           0.           0.\n",
      "   0.           0.           0.          31.           1.86966682] tensor(16005.)\n",
      "[  2.         197.           0.           1.          37.\n",
      " 121.           0.           2.           0.           0.\n",
      "   0.           0.           0.          33.           0.42423353] tensor(7776.9434)\n",
      "[  2.         311.           0.           1.          39.\n",
      " 116.           0.           2.           0.           0.\n",
      "   0.           0.           0.          31.          -0.70677457] tensor(5531.9990)\n",
      "[  1.         159.           1.           1.          34.\n",
      " 112.           0.           2.           0.           0.\n",
      "   0.           0.           0.          28.          -0.45927847] tensor(6000.)\n",
      "[   2.         1703.            0.            0.           45.\n",
      "  126.            0.            2.            0.            0.\n",
      "    0.            0.            0.           31.            1.84178959] tensor(15301.5059)\n",
      "[ 2.00000000e+00  7.34000000e+02  1.00000000e+00  1.00000000e+00\n",
      "  4.20000000e+01  8.60000000e+01  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  2.80000000e+01 -2.46441106e-01] tensor(6402.)\n",
      "[2.00000000e+00 5.54000000e+02 1.00000000e+00 1.00000000e+00\n",
      " 3.80000000e+01 1.14000000e+02 1.00000000e+00 0.00000000e+00\n",
      " 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00\n",
      " 0.00000000e+00 1.90000000e+01 2.00470543e-01] tensor(7288.6064)\n",
      "[  2.         160.           1.           1.          39.\n",
      " 119.           1.           0.           0.           0.\n",
      "   0.           0.           0.          31.           1.42012124] tensor(11063.9980)\n",
      "[4.00000000e+00 1.70300000e+03 0.00000000e+00 0.00000000e+00\n",
      " 4.20000000e+01 8.60000000e+01 0.00000000e+00 0.00000000e+00\n",
      " 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00\n",
      " 0.00000000e+00 3.30000000e+01 1.67065547e+00] tensor(12853.4453)\n",
      "[2.00000000e+00 6.52000000e+02 0.00000000e+00 1.00000000e+00\n",
      " 4.50000000e+01 1.26000000e+02 0.00000000e+00 2.00000000e+00\n",
      " 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00\n",
      " 0.00000000e+00 3.30000000e+01 2.00470543e-01] tensor(7288.6064)\n",
      "[ 2.00000000e+00  1.70300000e+03  0.00000000e+00  0.00000000e+00\n",
      "  3.60000000e+01  1.14000000e+02  0.00000000e+00  2.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  1.80000000e+01 -2.46441106e-01] tensor(6402.)\n",
      "[2.00000000e+00 2.60000000e+02 0.00000000e+00 1.00000000e+00\n",
      " 4.20000000e+01 8.60000000e+01 0.00000000e+00 0.00000000e+00\n",
      " 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00\n",
      " 0.00000000e+00 3.30000000e+01 2.00470543e-01] tensor(7288.6064)\n",
      "[  3.         747.           0.           1.          42.\n",
      "  86.           0.           0.           0.           0.\n",
      "   0.           0.           0.          21.           1.16739401] tensor(9916.5791)\n",
      "[  2.          54.           0.           1.          31.\n",
      " 118.           0.           2.           0.           0.\n",
      "   0.           0.           0.          33.          -0.88503262] tensor(5184.6289)\n",
      "[  2.         160.           1.           1.          31.\n",
      " 118.           1.           0.           0.           0.\n",
      "   0.           0.           0.          26.          -1.29818526] tensor(4268.)\n",
      "[ 1.00000000e+00  7.53000000e+02  0.00000000e+00  1.00000000e+00\n",
      "  3.60000000e+01  1.16000000e+02  0.00000000e+00  2.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  2.90000000e+01 -2.46441106e-01] tensor(6402.)\n",
      "[ 2.00000000e+00  8.42000000e+02  0.00000000e+00  1.00000000e+00\n",
      "  4.20000000e+01  8.60000000e+01  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  3.30000000e+01 -4.59278471e-01] tensor(6000.)\n",
      "[  2.         54.          0.          1.         45.        126.\n",
      "   0.          2.          0.          0.          0.          0.\n",
      "   0.         15.          1.2775747] tensor(10369.2578)\n",
      "[2.00000000e+00 1.44700000e+03 0.00000000e+00 1.00000000e+00\n",
      " 4.20000000e+01 8.60000000e+01 0.00000000e+00 0.00000000e+00\n",
      " 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00\n",
      " 0.00000000e+00 3.30000000e+01 1.03704191e+00] tensor(9447.1797)\n",
      "[ 2.00000000e+00  7.49000000e+02  0.00000000e+00  1.00000000e+00\n",
      "  3.90000000e+01  1.16000000e+02  1.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  3.10000000e+01 -2.48496109e-02] tensor(6830.9341)\n",
      "[  2.         552.           0.           1.          28.\n",
      " 116.           0.           2.           0.           0.\n",
      "   0.           0.           0.          31.          -0.88503262] tensor(5184.6289)\n",
      "[  1.         652.           0.           1.          23.\n",
      " 113.           0.           2.           0.           0.\n",
      "   0.           0.           0.          31.           1.86966682] tensor(16005.)\n",
      "[  1.         875.           0.           0.          36.\n",
      " 116.           0.           2.           0.           0.\n",
      "   0.           0.           0.          33.          -1.39501774] tensor(4000.)\n",
      "[  1.         530.           0.           1.          28.\n",
      " 115.           0.           2.           0.           0.\n",
      "   0.           0.           0.          33.          -1.18132525] tensor(4553.9561)\n",
      "[ 3.00000000e+00  9.44000000e+02  0.00000000e+00  1.00000000e+00\n",
      "  4.20000000e+01  8.60000000e+01  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  3.30000000e+01 -3.01143857e-01] tensor(6298.1201)\n",
      "[  1.         159.           1.           1.          39.\n",
      " 116.           0.           2.           0.           0.\n",
      "   0.           0.           0.          31.           0.73256683] tensor(8536.)\n",
      "[ 1.00000000e+00  5.17000000e+02  0.00000000e+00  0.00000000e+00\n",
      "  2.10000000e+01  1.10000000e+02  0.00000000e+00  2.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  3.00000000e+01 -3.01143857e-01] tensor(6298.1201)\n",
      "[ 2.00000000e+00  1.70300000e+03  0.00000000e+00  0.00000000e+00\n",
      "  3.10000000e+01  1.12000000e+02  1.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  3.30000000e+01 -1.39501774e+00] tensor(4000.)\n",
      "[  1.         159.           1.           1.          26.\n",
      " 119.           0.           2.           0.           0.\n",
      "   0.           0.           0.          21.          -1.18132525] tensor(4553.9561)\n",
      "[  2.         407.           1.           1.          32.\n",
      " 118.           0.           2.           0.           0.\n",
      "   0.           0.           0.          33.          -1.18132525] tensor(4553.9561)\n",
      "[  1.         652.           0.           1.          39.\n",
      " 116.           0.           2.           0.           0.\n",
      "   0.           0.           0.          33.           0.84684595] tensor(8853.9639)\n",
      "[  1.         348.           0.           1.          31.\n",
      " 120.           0.           2.           3.           3.\n",
      "   0.           0.           0.          26.          -0.51104337] tensor(5902.6431)\n",
      "[ 2.00000000e+00  1.70300000e+03  0.00000000e+00  0.00000000e+00\n",
      "  3.40000000e+01  1.15000000e+02  1.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  3.30000000e+01 -2.48496109e-02] tensor(6830.9341)\n",
      "[ 1.00000000e+00  8.40000000e+02  0.00000000e+00  1.00000000e+00\n",
      "  3.40000000e+01  1.05000000e+02  0.00000000e+00  2.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  2.70000000e+01 -7.06774568e-01] tensor(5531.9990)\n",
      "[  1.        652.          0.          1.         42.         86.\n",
      "   0.          0.          0.          0.          0.          0.\n",
      "   0.         31.          1.9010312] tensor(17077.3359)\n",
      "[  1.         159.           1.           1.          42.\n",
      "  86.           0.           0.           0.           0.\n",
      "   0.           0.           0.          31.           0.42423353] tensor(7776.9434)\n",
      "[1.20000000e+01 6.49000000e+02 0.00000000e+00 1.00000000e+00\n",
      " 2.80000000e+01 1.12000000e+02 0.00000000e+00 2.00000000e+00\n",
      " 3.00000000e+00 3.00000000e+00 0.00000000e+00 0.00000000e+00\n",
      " 3.00000000e+00 3.00000000e+01 3.68223674e-01] tensor(7650.7529)\n",
      "[  1.         635.           0.           1.          21.\n",
      " 110.           0.           2.           0.           0.\n",
      "   0.           0.           0.          29.          -1.04358761] tensor(4859.0713)\n",
      "[  1.         652.           0.           1.          31.\n",
      " 121.           0.           2.           0.           0.\n",
      "   0.           0.           0.          33.          -1.04358761] tensor(4859.0713)\n",
      "[ 1.00000000e+00  8.73000000e+02  0.00000000e+00  0.00000000e+00\n",
      "  3.90000000e+01  1.16000000e+02  0.00000000e+00  2.00000000e+00\n",
      "  3.00000000e+00  3.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  3.30000000e+01 -5.11043371e-01] tensor(5902.6431)\n",
      "[1.00000000e+00 7.18000000e+02 0.00000000e+00 1.00000000e+00\n",
      " 4.20000000e+01 8.60000000e+01 0.00000000e+00 0.00000000e+00\n",
      " 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00\n",
      " 0.00000000e+00 2.70000000e+01 2.00470543e-01] tensor(7288.6064)\n",
      "[ 1.00000000e+00  6.52000000e+02  0.00000000e+00  1.00000000e+00\n",
      "  4.20000000e+01  8.60000000e+01  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  3.00000000e+01 -2.46441106e-01] tensor(6402.)\n",
      "[1.00000000e+00 2.57000000e+02 1.00000000e+00 1.00000000e+00\n",
      " 2.80000000e+01 1.15000000e+02 0.00000000e+00 2.00000000e+00\n",
      " 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00\n",
      " 0.00000000e+00 3.10000000e+01 2.00470543e-01] tensor(7288.6064)\n",
      "[  1.         407.           1.           1.          37.\n",
      " 112.           0.           2.           3.           3.\n",
      "   0.           0.           0.          29.           1.36054634] tensor(10755.5107)\n",
      "[  1.         348.           0.           1.          26.\n",
      " 119.           0.           2.           0.           0.\n",
      "   0.           0.           0.          33.          -0.70677457] tensor(5531.9990)\n",
      "[  1.         257.           1.           1.          39.\n",
      " 117.           0.           2.           3.           0.\n",
      "   0.           0.           0.          33.          -1.18132525] tensor(4553.9561)\n",
      "[  1.         407.           1.           1.          30.\n",
      " 120.           0.           2.           0.           0.\n",
      "   0.           0.           0.          33.           1.86015571] tensor(15745.2998)\n",
      "[  1.         159.           1.           1.          38.\n",
      " 106.           0.           2.           0.           0.\n",
      "   0.           0.           0.          33.          -1.39501774] tensor(4000.)\n",
      "[1.00000000e+00 7.18000000e+02 0.00000000e+00 1.00000000e+00\n",
      " 3.90000000e+01 1.17000000e+02 0.00000000e+00 2.00000000e+00\n",
      " 3.00000000e+00 3.00000000e+00 0.00000000e+00 0.00000000e+00\n",
      " 3.00000000e+00 2.20000000e+01 4.24233531e-01] tensor(7776.9434)\n",
      "[  1.          28.           0.           1.          33.\n",
      " 114.           0.           2.           0.           0.\n",
      "   0.           0.           0.          33.          -1.18132525] tensor(4553.9561)\n",
      "[ 2.00000000e+00  5.52000000e+02  0.00000000e+00  1.00000000e+00\n",
      "  3.50000000e+01  1.11000000e+02  1.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  1.60000000e+01 -5.11043371e-01] tensor(5902.6431)\n",
      "[  1.         407.           1.           1.          39.\n",
      " 119.           0.           2.           0.           0.\n",
      "   0.           0.           0.          33.          -0.45927847] tensor(6000.)\n",
      "[ 1.00000000e+00  1.70300000e+03  0.00000000e+00  0.00000000e+00\n",
      "  3.00000000e+01  1.20000000e+02  0.00000000e+00  2.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  3.30000000e+01 -2.48496109e-02] tensor(6830.9341)\n",
      "[ 12.         944.           0.           1.          39.\n",
      " 116.           0.           2.           3.           3.\n",
      "   0.           0.           3.          31.           1.95140677] tensor(20744.9961)\n",
      "[  2.         410.           0.           1.          31.\n",
      " 121.           1.           0.           0.           0.\n",
      "   0.           0.           0.          31.          -1.18132525] tensor(4553.9561)\n",
      "[  2.         257.           1.           1.          42.\n",
      "  86.           0.           0.           0.           0.\n",
      "   0.           0.           0.          21.          -1.04358761] tensor(4859.0713)\n",
      "[1.00000000e+00 1.70300000e+03 0.00000000e+00 0.00000000e+00\n",
      " 3.20000000e+01 1.18000000e+02 0.00000000e+00 2.00000000e+00\n",
      " 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00\n",
      " 0.00000000e+00 2.60000000e+01 2.00470543e-01] tensor(7288.6064)\n",
      "[  1.          57.           0.           1.          36.\n",
      " 117.           0.           2.           3.           3.\n",
      "   0.           0.           3.          22.           0.73256683] tensor(8536.)\n",
      "[  1.         348.           0.           1.          26.\n",
      " 100.           0.           2.           3.           3.\n",
      "   0.           0.           0.          33.           0.36822367] tensor(7650.7529)\n",
      "[ 2.00000000e+00  8.51000000e+02  0.00000000e+00  1.00000000e+00\n",
      "  3.60000000e+01  1.18000000e+02  0.00000000e+00  2.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  3.30000000e+01 -7.06774568e-01] tensor(5531.9990)\n",
      "[1.00000000e+00 2.57000000e+02 1.00000000e+00 1.00000000e+00\n",
      " 2.80000000e+01 1.15000000e+02 0.00000000e+00 2.00000000e+00\n",
      " 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00\n",
      " 0.00000000e+00 2.80000000e+01 2.00470543e-01] tensor(7288.6064)\n",
      "[ 1.00000000e+00  7.69000000e+02  0.00000000e+00  0.00000000e+00\n",
      "  3.40000000e+01  1.13000000e+02  0.00000000e+00  2.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  1.70000000e+01 -2.46441106e-01] tensor(6402.)\n",
      "[  1.         842.           0.           1.          42.\n",
      "  86.           0.           0.           0.           0.\n",
      "   0.           0.           0.          26.          -1.29818526] tensor(4268.)\n",
      "[ 2.00000000e+00  1.70300000e+03  0.00000000e+00  0.00000000e+00\n",
      "  4.70000000e+01  1.23000000e+02  0.00000000e+00  2.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  2.40000000e+01 -8.13051736e-02] tensor(6720.0938)\n",
      "[ 2.00000000e+00  8.54000000e+02  0.00000000e+00  0.00000000e+00\n",
      "  4.20000000e+01  8.60000000e+01  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  3.00000000e+01 -7.06774568e-01] tensor(5531.9990)\n",
      "[  1.         747.           0.           1.          30.\n",
      " 103.           0.           2.           0.           0.\n",
      "   0.           0.           0.          31.           1.20889385] tensor(10080.1406)\n",
      "[1.00000000e+00 6.35000000e+02 0.00000000e+00 1.00000000e+00\n",
      " 2.80000000e+01 1.15000000e+02 0.00000000e+00 2.00000000e+00\n",
      " 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00\n",
      " 0.00000000e+00 3.00000000e+01 4.24233531e-01] tensor(7776.9434)\n",
      "[ 1.00000000e+00  4.07000000e+02  1.00000000e+00  1.00000000e+00\n",
      "  4.20000000e+01  8.60000000e+01  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  3.30000000e+01 -3.01143857e-01] tensor(6298.1201)\n",
      "[ 1.00000000e+00  8.37000000e+02  0.00000000e+00  1.00000000e+00\n",
      "  3.90000000e+01  1.21000000e+02  0.00000000e+00  2.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  3.10000000e+01 -2.46441106e-01] tensor(6402.)\n",
      "[ 1.00000000e+00  1.70300000e+03  0.00000000e+00  0.00000000e+00\n",
      "  1.80000000e+01  1.09000000e+02  0.00000000e+00  2.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  5.00000000e+00 -5.11043371e-01] tensor(5902.6431)\n",
      "[ 3.00000000e+00  7.34000000e+02  1.00000000e+00  1.00000000e+00\n",
      "  4.20000000e+01  8.60000000e+01  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  3.10000000e+01 -5.11043371e-01] tensor(5902.6431)\n",
      "[  1.         944.           0.           1.          36.\n",
      " 114.           0.           2.           0.           0.\n",
      "   0.           0.           0.          33.           1.42012124] tensor(11063.9980)\n",
      "[  2.         161.           0.           1.          27.\n",
      " 112.           0.           2.           0.           0.\n",
      "   0.           0.           0.          33.           1.84178959] tensor(15301.5059)\n",
      "[  2.         737.           0.           1.          43.\n",
      " 126.           1.           0.           0.           0.\n",
      "   0.           0.           0.          33.           1.34300582] tensor(10670.)\n",
      "[ 2.00000000e+00  1.70300000e+03  0.00000000e+00  0.00000000e+00\n",
      "  3.00000000e+01  1.14000000e+02  1.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  2.50000000e+01 -1.18132525e+00] tensor(4553.9561)\n",
      "[  2.         851.           0.           1.          23.\n",
      " 113.           1.           0.           0.           0.\n",
      "   0.           0.           0.          30.          -1.04358761] tensor(4859.0713)\n",
      "[ 1.00000000e+00  3.48000000e+02  0.00000000e+00  1.00000000e+00\n",
      "  4.30000000e+01  8.70000000e+01  0.00000000e+00  2.00000000e+00\n",
      "  3.00000000e+00  3.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  3.30000000e+01 -8.13051736e-02] tensor(6720.0938)\n",
      "[ 6.00000000e+00  1.70300000e+03  0.00000000e+00  0.00000000e+00\n",
      "  4.20000000e+01  8.60000000e+01  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  3.10000000e+01 -5.11043371e-01] tensor(5902.6431)\n",
      "[  2.         543.           0.           1.          42.\n",
      "  86.           0.           0.           0.           0.\n",
      "   0.           0.           0.          25.           1.72544904] tensor(13440.1875)\n",
      "[ 2.00000000e+00  1.45000000e+03  0.00000000e+00  1.00000000e+00\n",
      "  4.30000000e+01  1.25000000e+02  0.00000000e+00  2.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  3.30000000e+01 -1.39501774e+00] tensor(4000.)\n",
      "[  1.         285.           0.           1.          26.\n",
      " 119.           0.           2.           0.           0.\n",
      "   0.           0.           0.          21.          -1.18132525] tensor(4553.9561)\n",
      "[  1.         162.           0.           1.          33.\n",
      " 113.           0.           2.           0.           0.\n",
      "   0.           0.           0.          18.          -1.39501774] tensor(4000.)\n",
      "[  2.         839.           0.           1.          29.\n",
      " 105.           0.           2.           0.           0.\n",
      "   0.           0.           0.          33.          -1.39501774] tensor(4000.)\n",
      "[ 1.00000000e+00  1.70300000e+03  0.00000000e+00  0.00000000e+00\n",
      "  4.50000000e+01  1.26000000e+02  0.00000000e+00  2.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  1.50000000e+01 -1.18132525e+00] tensor(4553.9561)\n",
      "[  2.         874.           0.           1.          22.\n",
      " 113.           1.           0.           0.           0.\n",
      "   0.           0.           0.          33.          -1.29818526] tensor(4268.)\n",
      "[  1.        160.          1.          1.         40.        120.\n",
      "   0.          2.          0.          0.          0.          0.\n",
      "   0.         31.          1.9010312] tensor(17077.3359)\n",
      "[2.00000000e+00 7.34000000e+02 1.00000000e+00 1.00000000e+00\n",
      " 3.20000000e+01 1.18000000e+02 1.00000000e+00 0.00000000e+00\n",
      " 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00\n",
      " 0.00000000e+00 3.10000000e+01 2.00470543e-01] tensor(7288.6064)\n",
      "[  1.         652.           0.           1.          42.\n",
      "  86.           0.           0.           0.           0.\n",
      "   0.           0.           0.          20.          -0.70677457] tensor(5531.9990)\n",
      "[  1.         159.           1.           1.          42.\n",
      "  86.           0.           0.           0.           0.\n",
      "   0.           0.           0.          33.           1.20889385] tensor(10080.1406)\n",
      "[ 6.00000000e+00  8.06000000e+02  0.00000000e+00  1.00000000e+00\n",
      "  2.80000000e+01  1.15000000e+02  1.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  3.00000000e+01 -7.06774568e-01] tensor(5531.9990)\n",
      "[  2.          10.           0.           1.          29.\n",
      " 104.           0.           2.           0.           0.\n",
      "   0.           0.           0.          33.           1.64302154] tensor(12596.2402)\n",
      "[  1.         348.           0.           1.          40.\n",
      " 116.           0.           2.           3.           3.\n",
      "   0.           0.           0.          31.          -0.70677457] tensor(5531.9990)\n",
      "[  1.          10.           0.           1.          35.\n",
      " 113.           0.           2.           0.           0.\n",
      "   0.           0.           0.          33.          -1.39501774] tensor(4000.)\n",
      "[ 1.00000000e+00  1.70300000e+03  0.00000000e+00  0.00000000e+00\n",
      "  4.40000000e+01  8.60000000e+01  0.00000000e+00  2.00000000e+00\n",
      "  3.00000000e+00  3.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  7.00000000e+00 -1.29818526e+00] tensor(4268.)\n",
      "[1.00000000e+00 8.42000000e+02 0.00000000e+00 1.00000000e+00\n",
      " 2.60000000e+01 1.19000000e+02 0.00000000e+00 2.00000000e+00\n",
      " 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00\n",
      " 0.00000000e+00 3.30000000e+01 7.32566829e-01] tensor(8536.)\n",
      "[  2.         629.           0.           1.          34.\n",
      " 115.           0.           2.           0.           0.\n",
      "   0.           0.           0.          33.          -1.29818526] tensor(4268.)\n",
      "[  1.         842.           0.           1.          42.\n",
      "  86.           0.           0.           0.           0.\n",
      "   0.           0.           0.          30.           0.93187116] tensor(9107.9121)\n",
      "[  2.         465.           0.           1.          42.\n",
      "  86.           0.           0.           0.           0.\n",
      "   0.           0.           0.          33.          -0.70677457] tensor(5531.9990)\n",
      "[  1.         311.           0.           1.          42.\n",
      "  86.           0.           0.           0.           0.\n",
      "   0.           0.           0.          33.          -1.04358761] tensor(4859.0713)\n",
      "[ 2.00000000e+00  7.34000000e+02  1.00000000e+00  1.00000000e+00\n",
      "  3.70000000e+01  1.12000000e+02  1.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  2.60000000e+01 -4.59278471e-01] tensor(6000.)\n",
      "[  1.        718.          0.          1.         30.        114.\n",
      "   0.          2.          0.          0.          0.          0.\n",
      "   0.         31.          1.9010312] tensor(17077.3359)\n",
      "[1.00000000e+00 7.54000000e+02 0.00000000e+00 1.00000000e+00\n",
      " 4.00000000e+01 1.16000000e+02 0.00000000e+00 2.00000000e+00\n",
      " 3.00000000e+00 3.00000000e+00 0.00000000e+00 0.00000000e+00\n",
      " 0.00000000e+00 3.30000000e+01 3.68223674e-01] tensor(7650.7529)\n",
      "[  1.         652.           0.           1.          31.\n",
      " 121.           0.           2.           0.           0.\n",
      "   0.           0.           0.          33.           1.18880493] tensor(10000.)\n",
      "[  1.         407.           1.           1.          38.\n",
      " 117.           0.           2.           0.           0.\n",
      "   0.           0.           0.          33.          -1.04358761] tensor(4859.0713)\n",
      "[  1.         257.           1.           1.          42.\n",
      "  86.           0.           0.           0.           0.\n",
      "   0.           0.           0.          31.           1.97065282] tensor(28462.2246)\n",
      "[1.00000000e+00 7.47000000e+02 0.00000000e+00 1.00000000e+00\n",
      " 3.40000000e+01 1.08000000e+02 0.00000000e+00 2.00000000e+00\n",
      " 3.00000000e+00 3.00000000e+00 0.00000000e+00 0.00000000e+00\n",
      " 3.00000000e+00 3.30000000e+01 1.43569229e-01] tensor(7170.3403)\n",
      "[2.00000000e+00 8.51000000e+02 0.00000000e+00 1.00000000e+00\n",
      " 3.40000000e+01 1.13000000e+02 1.00000000e+00 0.00000000e+00\n",
      " 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00\n",
      " 0.00000000e+00 3.30000000e+01 7.32566829e-01] tensor(8536.)\n",
      "[  1.         753.           0.           1.          41.\n",
      " 123.           0.           2.           0.           0.\n",
      "   0.           0.           0.          33.          -1.18132525] tensor(4553.9561)\n",
      "[2.00000000e+00 8.37000000e+02 0.00000000e+00 1.00000000e+00\n",
      " 4.20000000e+01 8.60000000e+01 0.00000000e+00 0.00000000e+00\n",
      " 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00\n",
      " 0.00000000e+00 3.30000000e+01 7.32566829e-01] tensor(8536.)\n",
      "[  1.         649.           0.           1.          30.\n",
      " 114.           0.           2.           0.           0.\n",
      "   0.           0.           0.          31.          -0.88503262] tensor(5184.6289)\n",
      "[  1.         753.           0.           1.          40.\n",
      " 120.           0.           2.           0.           0.\n",
      "   0.           0.           0.          31.           0.93187116] tensor(9107.9121)\n",
      "[  2.           9.           0.           1.          31.\n",
      " 118.           1.           0.           0.           0.\n",
      "   0.           0.           0.          33.           0.42423353] tensor(7776.9434)\n",
      "[  1.         159.           1.           1.          40.\n",
      " 116.           0.           2.           3.           3.\n",
      "   0.           0.           0.          33.           0.20047054] tensor(7288.6064)\n",
      "[  1.         944.           0.           1.          39.\n",
      " 118.           0.           2.           0.           0.\n",
      "   0.           0.           0.          31.          -1.04358761] tensor(4859.0713)\n",
      "[   2.         1703.            0.            0.           42.\n",
      "   86.            0.            0.            0.            0.\n",
      "    0.            0.            0.           30.            1.86966682] tensor(16005.)\n",
      "[  2.         842.           0.           1.          37.\n",
      " 114.           1.           0.           0.           0.\n",
      "   0.           0.           0.          33.           0.93187116] tensor(9107.9121)\n",
      "[  1.         840.           0.           1.          41.\n",
      " 123.           0.           2.           0.           0.\n",
      "   0.           0.           0.          33.          -1.29818526] tensor(4268.)\n",
      "[2.00000000e+00 2.57000000e+02 1.00000000e+00 1.00000000e+00\n",
      " 3.30000000e+01 1.19000000e+02 1.00000000e+00 0.00000000e+00\n",
      " 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00\n",
      " 0.00000000e+00 2.60000000e+01 2.00470543e-01] tensor(7288.6064)\n",
      "[  1.         554.           1.           1.          21.\n",
      " 110.           0.           2.           0.           0.\n",
      "   0.           0.           0.          30.           0.93187116] tensor(9107.9121)\n",
      "[1.0000000e+00 6.5200000e+02 0.0000000e+00 1.0000000e+00 4.2000000e+01\n",
      " 8.6000000e+01 0.0000000e+00 0.0000000e+00 0.0000000e+00 0.0000000e+00\n",
      " 0.0000000e+00 0.0000000e+00 0.0000000e+00 3.3000000e+01 5.1998844e-01] tensor(8000.)\n",
      "[  2.         554.           1.           1.          34.\n",
      " 109.           1.           0.           0.           0.\n",
      "   0.           0.           0.          31.          -1.39501774] tensor(4000.)\n",
      "[  1.         260.           0.           1.          36.\n",
      " 117.           0.           2.           0.           0.\n",
      "   0.           0.           0.          33.          -0.51104337] tensor(5902.6431)\n",
      "[  2.         851.           0.           1.          42.\n",
      "  86.           0.           0.           0.           0.\n",
      "   0.           0.           0.          27.          -0.88503262] tensor(5184.6289)\n",
      "[  2.         652.           0.           1.          42.\n",
      "  86.           0.           0.           0.           0.\n",
      "   0.           0.           0.          31.           1.46025561] tensor(11289.9160)\n",
      "[  2.         407.           1.           1.          39.\n",
      " 117.           1.           0.           0.           0.\n",
      "   0.           0.           0.          22.           1.11436842] tensor(9718.1426)\n",
      "[  1.         870.           0.           1.          30.\n",
      " 114.           0.           2.           0.           0.\n",
      "   0.           0.           0.          29.          -1.04358761] tensor(4859.0713)\n",
      "[  2.         747.           0.           1.          36.\n",
      " 117.           1.           0.           0.           0.\n",
      "   0.           0.           0.          33.          -1.29818526] tensor(4268.)\n",
      "[  1.         720.           0.           1.          39.\n",
      " 117.           0.           2.           0.           0.\n",
      "   0.           0.           0.          33.          -1.18132525] tensor(4553.9561)\n",
      "[  1.         842.           0.           1.          30.\n",
      " 103.           0.           2.           3.           3.\n",
      "   0.           0.           0.          33.          -1.04358761] tensor(4859.0713)\n",
      "[  1.         842.           0.           1.          32.\n",
      " 118.           0.           2.           3.           3.\n",
      "   4.           0.           3.          33.          -1.39501774] tensor(4000.)\n",
      "[ 1.00000000e+00  3.11000000e+02  0.00000000e+00  1.00000000e+00\n",
      "  4.20000000e+01  8.60000000e+01  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  3.30000000e+01 -3.01143857e-01] tensor(6298.1201)\n",
      "[ 2.00000000e+00  1.70300000e+03  0.00000000e+00  0.00000000e+00\n",
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      "  0.00000000e+00  3.30000000e+01 -4.59278471e-01] tensor(6000.)\n",
      "[ 2.00000000e+00  5.54000000e+02  1.00000000e+00  1.00000000e+00\n",
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      "  0.00000000e+00  3.30000000e+01 -2.48496109e-02] tensor(6830.9341)\n",
      "[  2.         734.           1.           1.          39.\n",
      " 117.           1.           0.           0.           0.\n",
      "   0.           0.           0.          22.          -1.18132525] tensor(4553.9561)\n",
      "[ 11.         407.           1.           1.          42.\n",
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      "   0.           0.           0.          31.          -0.88503262] tensor(5184.6289)\n",
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      "  0.00000000e+00  3.10000000e+01 -4.59278471e-01] tensor(6000.)\n",
      "[  2.         554.           1.           1.          34.\n",
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      "[  1.         411.           0.           1.          28.\n",
      " 115.           0.           2.           0.           0.\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "   0.           0.           0.          33.          -0.88503262] tensor(5184.6289)\n",
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      "[  2.         944.           0.           1.          23.\n",
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      "[ 12.         160.           1.           1.          30.\n",
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      "[  2.         851.           0.           1.          36.\n",
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      "[  1.         160.           1.           1.          28.\n",
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      "[  2.          10.           0.           1.          34.\n",
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      "[  2.         166.           0.           1.          29.\n",
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      "[  2.         814.           0.           1.          32.\n",
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      "[  1.         407.           1.           1.          29.\n",
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      "[ 12.         753.           0.           1.          29.\n",
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      "[  1.         747.           0.           1.          23.\n",
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      "[  1.         159.           1.           1.          30.\n",
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      "[ 2.00000000e+00  1.70300000e+03  0.00000000e+00  0.00000000e+00\n",
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      "[  2.         944.           0.           1.          23.\n",
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      "[  1.         736.           0.           1.          31.\n",
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      "[  2.         162.           0.           1.          40.\n",
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      "[  2.         629.           0.           1.          40.\n",
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      "[ 1.00000000e+00  7.47000000e+02  0.00000000e+00  1.00000000e+00\n",
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      "[ 2.00000000e+00  4.07000000e+02  1.00000000e+00  1.00000000e+00\n",
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      "  0.00000000e+00  3.30000000e+01 -2.46441106e-01] tensor(6402.)\n",
      "[1.00000000e+00 7.39000000e+02 0.00000000e+00 1.00000000e+00\n",
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      " 0.00000000e+00 2.40000000e+01 7.32566829e-01] tensor(8536.)\n",
      "[  2.        752.          0.          1.         31.        118.\n",
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      "[  8.         160.           1.           1.          32.\n",
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      "[  2.         852.           0.           1.          30.\n",
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      "[  2.         841.           0.           1.          29.\n",
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      "[  2.         851.           0.           1.          42.\n",
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      "[  2.         257.           1.           1.          23.\n",
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      "[ 2.00000000e+00  1.70300000e+03  0.00000000e+00  0.00000000e+00\n",
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      "[ 1.10000000e+01  1.59000000e+02  1.00000000e+00  1.00000000e+00\n",
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      "[2.00000000e+00 1.70300000e+03 0.00000000e+00 0.00000000e+00\n",
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      " 0.00000000e+00 3.10000000e+01 1.43569229e-01] tensor(7170.3403)\n",
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      " 0.00000000e+00 3.10000000e+01 1.69171182e+00] tensor(13065.4473)\n",
      "[  2.         160.           1.           1.          45.\n",
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      "[  2.         160.           1.           1.          31.\n",
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      "[  2.         852.           0.           1.          23.\n",
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      "[  1.        748.          0.          1.         29.        106.\n",
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      "[ 3.00000000e+00  9.44000000e+02  0.00000000e+00  1.00000000e+00\n",
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      "[  1.         748.           0.           1.          35.\n",
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      "[ 12.         856.           0.           1.          39.\n",
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      "[ 2.00000000e+00  8.52000000e+02  0.00000000e+00  1.00000000e+00\n",
      "  2.60000000e+01  1.06000000e+02  0.00000000e+00  2.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  3.30000000e+01 -2.46441106e-01] tensor(6402.)\n",
      "[  2.         554.           1.           1.          30.\n",
      " 114.           0.           2.           0.           0.\n",
      "   0.           0.           0.          33.          -1.18132525] tensor(4553.9561)\n",
      "[ 1.00000000e+00  8.51000000e+02  0.00000000e+00  1.00000000e+00\n",
      "  3.20000000e+01  1.18000000e+02  0.00000000e+00  2.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  2.60000000e+01 -2.48496109e-02] tensor(6830.9341)\n",
      "[ 1.00000000e+00  6.52000000e+02  0.00000000e+00  1.00000000e+00\n",
      "  3.20000000e+01  1.17000000e+02  0.00000000e+00  2.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  2.00000000e+01 -3.01143857e-01] tensor(6298.1201)\n",
      "[ 12.         652.           0.           1.          34.\n",
      " 113.           0.           2.           3.           3.\n",
      "   0.           0.           0.          33.          -1.18132525] tensor(4553.9561)\n",
      "[ 2.00000000e+00  1.44800000e+03  0.00000000e+00  1.00000000e+00\n",
      "  4.50000000e+01  1.26000000e+02  1.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  1.50000000e+01 -1.04358761e+00] tensor(4859.0713)\n",
      "[ 1.00000000e+00  9.00000000e+00  0.00000000e+00  1.00000000e+00\n",
      "  3.00000000e+01  1.14000000e+02  0.00000000e+00  2.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  2.50000000e+01 -2.48496109e-02] tensor(6830.9341)\n",
      "[ 1.00000000e+00  1.70300000e+03  0.00000000e+00  0.00000000e+00\n",
      "  4.10000000e+01  1.23000000e+02  0.00000000e+00  2.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  3.30000000e+01 -8.85032618e-01] tensor(5184.6289)\n",
      "[  2.        635.          0.          1.         31.        118.\n",
      "   0.          2.          0.          0.          0.          0.\n",
      "   0.         33.          1.9010312] tensor(17077.3359)\n",
      "[  1.           9.           0.           1.          31.\n",
      " 117.           0.           2.           0.           0.\n",
      "   0.           0.           0.          31.           0.93187116] tensor(9107.9121)\n",
      "[ 2.00000000e+00  6.35000000e+02  0.00000000e+00  1.00000000e+00\n",
      "  3.10000000e+01  1.17000000e+02  1.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  2.00000000e+01 -2.46441106e-01] tensor(6402.)\n",
      "[  1.         407.           1.           1.          38.\n",
      " 112.           0.           2.           0.           0.\n",
      "   0.           0.           0.          33.           1.58881165] tensor(12147.6777)\n",
      "[ 2.00000000e+00  1.70300000e+03  0.00000000e+00  0.00000000e+00\n",
      "  3.80000000e+01  1.14000000e+02  0.00000000e+00  2.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  3.30000000e+01 -1.18132525e+00] tensor(4553.9561)\n",
      "[  2.         944.           0.           1.          39.\n",
      " 116.           1.           0.           0.           0.\n",
      "   0.           0.           0.          33.          -1.04358761] tensor(4859.0713)\n",
      "[  2.         407.           1.           1.          38.\n",
      " 114.           1.           0.           0.           0.\n",
      "   0.           0.           0.          31.           1.96709287] tensor(25000.)\n",
      "[  1.         635.           0.           1.          38.\n",
      " 115.           0.           2.           0.           0.\n",
      "   0.           0.           0.          31.           1.36054634] tensor(10755.5107)\n",
      "[  1.         734.           1.           1.          28.\n",
      " 115.           0.           2.           0.           0.\n",
      "   0.           0.           0.          33.          -1.18132525] tensor(4553.9561)\n",
      "[2.00000000e+00 1.70300000e+03 0.00000000e+00 0.00000000e+00\n",
      " 2.80000000e+01 1.12000000e+02 0.00000000e+00 2.00000000e+00\n",
      " 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00\n",
      " 0.00000000e+00 3.30000000e+01 1.11436842e+00] tensor(9718.1426)\n",
      "[  3.      407.        1.        1.       28.      112.        1.\n",
      "   0.        0.        0.        0.        0.        0.       19.\n",
      "   0.58742] tensor(8163.3535)\n",
      "[  2.         407.           1.           1.          42.\n",
      "  86.           0.           0.           0.           0.\n",
      "   0.           0.           0.          33.           1.92387304] tensor(18221.5156)\n",
      "[  2.         160.           1.           1.          26.\n",
      " 119.           1.           0.           0.           0.\n",
      "   0.           0.           0.          20.          -0.70677457] tensor(5531.9990)\n",
      "[ 2.00000000e+00  6.52000000e+02  0.00000000e+00  1.00000000e+00\n",
      "  2.80000000e+01  1.16000000e+02  1.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  3.00000000e+01 -5.11043371e-01] tensor(5902.6431)\n",
      "[  2.         160.           1.           1.          23.\n",
      " 113.           1.           0.           0.           0.\n",
      "   0.           0.           0.          31.          -0.45927847] tensor(6000.)\n",
      "[1.00000000e+00 4.11000000e+02 0.00000000e+00 1.00000000e+00\n",
      " 3.00000000e+01 1.13000000e+02 0.00000000e+00 2.00000000e+00\n",
      " 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00\n",
      " 0.00000000e+00 3.00000000e+01 3.68223674e-01] tensor(7650.7529)\n",
      "[  1.         749.           0.           1.          30.\n",
      " 104.           0.           2.           0.           0.\n",
      "   0.           0.           0.          33.          -1.29818526] tensor(4268.)\n",
      "[2.00000000e+00 1.70300000e+03 0.00000000e+00 0.00000000e+00\n",
      " 4.30000000e+01 1.26000000e+02 1.00000000e+00 0.00000000e+00\n",
      " 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00\n",
      " 0.00000000e+00 3.10000000e+01 9.31871161e-01] tensor(9107.9121)\n",
      "[2.00000000e+00 1.70300000e+03 0.00000000e+00 0.00000000e+00\n",
      " 2.90000000e+01 1.11000000e+02 1.00000000e+00 0.00000000e+00\n",
      " 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00\n",
      " 0.00000000e+00 3.30000000e+01 1.82760652e+00] tensor(15000.)\n",
      "[  1.         160.           1.           1.          42.\n",
      "  86.           0.           0.           0.           0.\n",
      "   0.           0.           0.          29.           0.73256683] tensor(8536.)\n",
      "[ 1.00000000e+00  1.70300000e+03  0.00000000e+00  0.00000000e+00\n",
      "  3.90000000e+01  1.21000000e+02  0.00000000e+00  2.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  2.40000000e+01 -1.04358761e+00] tensor(4859.0713)\n",
      "[  1.         151.           0.           1.          34.\n",
      " 117.           0.           2.           3.           3.\n",
      "   0.           0.           0.          33.           1.11436842] tensor(9718.1426)\n",
      "[2.00000000e+00 1.70300000e+03 0.00000000e+00 0.00000000e+00\n",
      " 3.00000000e+01 1.20000000e+02 1.00000000e+00 0.00000000e+00\n",
      " 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00\n",
      " 0.00000000e+00 3.30000000e+01 1.43569229e-01] tensor(7170.3403)\n",
      "[  1.         658.           0.           1.          42.\n",
      "  86.           0.           0.           0.           0.\n",
      "   0.           0.           0.          31.          -0.88503262] tensor(5184.6289)\n",
      "[ 1.00000000e+00  7.36000000e+02  0.00000000e+00  1.00000000e+00\n",
      "  3.40000000e+01  1.08000000e+02  0.00000000e+00  2.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  3.10000000e+01 -8.13051736e-02] tensor(6720.0938)\n",
      "[ 1.00000000e+00  7.20000000e+02  0.00000000e+00  1.00000000e+00\n",
      "  3.40000000e+01  1.09000000e+02  0.00000000e+00  2.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  3.10000000e+01 -7.06774568e-01] tensor(5531.9990)\n",
      "[  2.        554.          1.          1.         34.        117.\n",
      "   0.          2.          0.          0.          0.          0.\n",
      "   0.         33.          1.9010312] tensor(17077.3359)\n",
      "[2.00000000e+00 8.52000000e+02 0.00000000e+00 1.00000000e+00\n",
      " 3.90000000e+01 1.16000000e+02 0.00000000e+00 2.00000000e+00\n",
      " 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00\n",
      " 0.00000000e+00 3.10000000e+01 3.68223674e-01] tensor(7650.7529)\n",
      "[ 2.00000000e+00  1.70300000e+03  0.00000000e+00  0.00000000e+00\n",
      "  3.40000000e+01  1.09000000e+02  1.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  3.10000000e+01 -2.48496109e-02] tensor(6830.9341)\n",
      "[  2.         839.           0.           1.          29.\n",
      " 120.           1.           0.           0.           0.\n",
      "   0.           0.           0.          33.          -1.29818526] tensor(4268.)\n",
      "[ 1.00000000e+00  7.42000000e+02  0.00000000e+00  1.00000000e+00\n",
      "  3.40000000e+01  1.08000000e+02  0.00000000e+00  2.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  3.30000000e+01 -2.48496109e-02] tensor(6830.9341)\n",
      "[ 2.00000000e+00  8.40000000e+02  0.00000000e+00  1.00000000e+00\n",
      "  2.50000000e+01  1.02000000e+02  1.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  1.30000000e+01 -5.11043371e-01] tensor(5902.6431)\n",
      "[  1.          49.           0.           1.          28.\n",
      " 112.           0.           2.           0.           0.\n",
      "   0.           0.           0.          31.           1.11436842] tensor(9718.1426)\n",
      "[  1.         554.           1.           1.          36.\n",
      " 117.           0.           2.           0.           0.\n",
      "   0.           0.           0.          33.           0.93187116] tensor(9107.9121)\n",
      "[ 1.00000000e+00  6.58000000e+02  0.00000000e+00  1.00000000e+00\n",
      "  2.90000000e+01  1.20000000e+02  0.00000000e+00  2.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  3.30000000e+01 -5.11043371e-01] tensor(5902.6431)\n",
      "[2.00000000e+00 8.42000000e+02 0.00000000e+00 1.00000000e+00\n",
      " 3.60000000e+01 1.20000000e+02 1.00000000e+00 0.00000000e+00\n",
      " 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00\n",
      " 0.00000000e+00 3.00000000e+01 2.00470543e-01] tensor(7288.6064)\n",
      "[ 2.00000000e+00  7.30000000e+02  0.00000000e+00  1.00000000e+00\n",
      "  4.00000000e+01  1.17000000e+02  0.00000000e+00  2.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  3.30000000e+01 -2.46441106e-01] tensor(6402.)\n",
      "[  1.         753.           0.           1.          34.\n",
      " 108.           0.           2.           0.           0.\n",
      "   0.           0.           0.          31.           0.84684595] tensor(8853.9639)\n",
      "[2.00000000e+00 1.70300000e+03 0.00000000e+00 0.00000000e+00\n",
      " 4.20000000e+01 8.60000000e+01 0.00000000e+00 0.00000000e+00\n",
      " 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00\n",
      " 0.00000000e+00 3.00000000e+01 5.87419996e-01] tensor(8163.3535)\n",
      "[  2.         771.           0.           1.          38.\n",
      " 115.           0.           2.           0.           0.\n",
      "   0.           0.           0.          30.           1.11436842] tensor(9718.1426)\n",
      "[1.00000000e+00 1.70300000e+03 0.00000000e+00 0.00000000e+00\n",
      " 3.00000000e+01 1.14000000e+02 0.00000000e+00 2.00000000e+00\n",
      " 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00\n",
      " 0.00000000e+00 3.30000000e+01 1.82760652e+00] tensor(15000.)\n",
      "[  2.         852.           0.           1.          29.\n",
      " 117.           0.           2.           0.           0.\n",
      "   0.           0.           0.          33.          -1.29818526] tensor(4268.)\n",
      "[ 2.00000000e+00  8.40000000e+02  0.00000000e+00  1.00000000e+00\n",
      "  4.20000000e+01  8.60000000e+01  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  2.00000000e+01 -2.48496109e-02] tensor(6830.9341)\n",
      "[  2.         160.           1.           1.          29.\n",
      " 106.           1.           0.           0.           0.\n",
      "   0.           0.           0.          33.          -1.29818526] tensor(4268.)\n",
      "[2.00000000e+00 7.47000000e+02 0.00000000e+00 1.00000000e+00\n",
      " 3.60000000e+01 1.03000000e+02 0.00000000e+00 2.00000000e+00\n",
      " 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00\n",
      " 0.00000000e+00 3.30000000e+01 2.00470543e-01] tensor(7288.6064)\n",
      "[  1.         238.           0.           1.          21.\n",
      " 110.           0.           2.           0.           0.\n",
      "   0.           0.           0.          31.           1.42012124] tensor(11063.9980)\n",
      "[2.00000000e+00 1.42900000e+03 0.00000000e+00 1.00000000e+00\n",
      " 2.80000000e+01 1.12000000e+02 0.00000000e+00 2.00000000e+00\n",
      " 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00\n",
      " 0.00000000e+00 3.00000000e+01 9.31871161e-01] tensor(9107.9121)\n",
      "[ 2.00000000e+00  7.34000000e+02  1.00000000e+00  1.00000000e+00\n",
      "  3.30000000e+01  1.07000000e+02  0.00000000e+00  2.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  3.10000000e+01 -7.06774568e-01] tensor(5531.9990)\n",
      "[ 2.00000000e+00  1.70300000e+03  0.00000000e+00  0.00000000e+00\n",
      "  4.20000000e+01  8.60000000e+01  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  3.30000000e+01 -2.48496109e-02] tensor(6830.9341)\n",
      "[  2.         162.           0.           1.          46.\n",
      " 126.           0.           2.           0.           0.\n",
      "   0.           0.           0.          33.          -0.24644111] tensor(6402.)\n",
      "[  1.         839.           0.           1.          30.\n",
      " 103.           0.           2.           3.           3.\n",
      "   0.           0.           0.          31.           1.47629237] tensor(11384.8896)\n",
      "[ 2.00000000e+00  1.19100000e+03  0.00000000e+00  0.00000000e+00\n",
      "  3.50000000e+01  1.13000000e+02  0.00000000e+00  2.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  2.20000000e+01 -7.06774568e-01] tensor(5531.9990)\n",
      "[  2.         260.           0.           1.          42.\n",
      "  86.           0.           0.           0.           0.\n",
      "   0.           0.           0.          33.          -1.39501774] tensor(4000.)\n",
      "[  2.         747.           0.           1.          38.\n",
      " 117.           1.           0.           0.           0.\n",
      "   0.           0.           0.          30.           1.86966682] tensor(16005.)\n",
      "[ 2.00000000e+00  8.40000000e+02  0.00000000e+00  1.00000000e+00\n",
      "  3.00000000e+01  1.20000000e+02  1.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  3.10000000e+01 -7.06774568e-01] tensor(5531.9990)\n",
      "[1.0000000e+00 1.7030000e+03 0.0000000e+00 0.0000000e+00 2.3000000e+01\n",
      " 1.1300000e+02 0.0000000e+00 2.0000000e+00 0.0000000e+00 0.0000000e+00\n",
      " 0.0000000e+00 0.0000000e+00 0.0000000e+00 3.0000000e+01 5.1998844e-01] tensor(8000.)\n",
      "[  1.         45.          0.          1.         23.        116.\n",
      "   0.          2.          0.          0.          0.          0.\n",
      "   0.         30.          0.6412624] tensor(8297.9980)\n",
      "[  2.         554.           1.           1.          35.\n",
      " 120.           0.           2.           0.           0.\n",
      "   0.           0.           0.          23.          -0.88503262] tensor(5184.6289)\n",
      "[3.00000000e+00 8.40000000e+02 0.00000000e+00 1.00000000e+00\n",
      " 4.20000000e+01 8.60000000e+01 0.00000000e+00 0.00000000e+00\n",
      " 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00\n",
      " 0.00000000e+00 3.30000000e+01 2.00470543e-01] tensor(7288.6064)\n",
      "[ 1.00000000e+00  6.35000000e+02  0.00000000e+00  1.00000000e+00\n",
      "  3.90000000e+01  1.17000000e+02  0.00000000e+00  2.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  2.20000000e+01 -4.59278471e-01] tensor(6000.)\n",
      "[2.00000000e+00 1.44700000e+03 0.00000000e+00 1.00000000e+00\n",
      " 4.20000000e+01 8.60000000e+01 0.00000000e+00 0.00000000e+00\n",
      " 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00\n",
      " 0.00000000e+00 3.00000000e+01 1.18880493e+00] tensor(10000.)\n",
      "[ 1.00000000e+00  8.52000000e+02  0.00000000e+00  1.00000000e+00\n",
      "  3.20000000e+01  1.18000000e+02  0.00000000e+00  2.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  3.30000000e+01 -5.11043371e-01] tensor(5902.6431)\n",
      "[1.00000000e+00 8.37000000e+02 0.00000000e+00 1.00000000e+00\n",
      " 3.00000000e+01 1.14000000e+02 0.00000000e+00 2.00000000e+00\n",
      " 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00\n",
      " 0.00000000e+00 3.00000000e+01 6.41262404e-01] tensor(8297.9980)\n",
      "[ 1.         26.          0.          1.         42.         86.\n",
      "  0.          0.          0.          0.          0.          0.\n",
      "  0.         33.         -0.30114386] tensor(6298.1201)\n",
      "[  1.        257.          1.          1.         42.         86.\n",
      "   0.          0.          0.          0.          0.          0.\n",
      "   0.         31.          0.6412624] tensor(8297.9980)\n",
      "[  1.         635.           0.           1.          38.\n",
      " 121.           0.           2.           0.           0.\n",
      "   0.           0.           0.          31.           0.73256683] tensor(8536.)\n",
      "[  2.         172.           0.           1.          42.\n",
      "  86.           0.           0.           0.           0.\n",
      "   0.           0.           0.          33.           1.20889385] tensor(10080.1406)\n",
      "[ 1.00000000e+00  2.97000000e+02  0.00000000e+00  1.00000000e+00\n",
      "  2.50000000e+01  1.10000000e+02  0.00000000e+00  2.00000000e+00\n",
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      "  0.00000000e+00  3.30000000e+01 -2.48496109e-02] tensor(6830.9341)\n",
      "[  1.         407.           1.           1.          35.\n",
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      "   0.           0.           0.          31.           1.58881165] tensor(12147.6777)\n",
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      "  0.00000000e+00  3.30000000e+01 -4.59278471e-01] tensor(6000.)\n",
      "[ 1.00000000e+00  1.70300000e+03  0.00000000e+00  0.00000000e+00\n",
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      "  0.00000000e+00  2.10000000e+01 -2.48496109e-02] tensor(6830.9341)\n",
      "[  1.         178.           0.           1.          34.\n",
      " 108.           0.           2.           0.           0.\n",
      "   0.           0.           0.          33.          -0.51104337] tensor(5902.6431)\n",
      "[  2.          57.           0.           1.          30.\n",
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      " 4.20000000e+01 8.60000000e+01 0.00000000e+00 0.00000000e+00\n",
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      " 0.00000000e+00 3.30000000e+01 1.64302154e+00] tensor(12596.2402)\n",
      "[  2.         652.           0.           1.          42.\n",
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      "   0.           0.           0.          33.          -1.04358761] tensor(4859.0713)\n",
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      "  0.00000000e+00  1.60000000e+01 -1.39501774e+00] tensor(4000.)\n",
      "[ 2.00000000e+00  1.60000000e+02  1.00000000e+00  1.00000000e+00\n",
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      "  0.00000000e+00  3.30000000e+01 -2.48496109e-02] tensor(6830.9341)\n",
      "[ 1.00000000e+00  6.49000000e+02  0.00000000e+00  1.00000000e+00\n",
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      "  0.00000000e+00  1.90000000e+01 -5.11043371e-01] tensor(5902.6431)\n",
      "[  2.         162.           0.           1.          25.\n",
      " 119.           0.           2.           0.           0.\n",
      "   0.           0.           0.          33.          -0.24644111] tensor(6402.)\n",
      "[  2.         530.           0.           1.          25.\n",
      " 114.           1.           0.           0.           0.\n",
      "   0.           0.           0.          30.          -0.88503262] tensor(5184.6289)\n",
      "[4.00000000e+00 1.70300000e+03 0.00000000e+00 0.00000000e+00\n",
      " 4.20000000e+01 8.60000000e+01 0.00000000e+00 0.00000000e+00\n",
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      " 0.00000000e+00 3.10000000e+01 4.24233531e-01] tensor(7776.9434)\n",
      "[1.00000000e+00 7.18000000e+02 0.00000000e+00 1.00000000e+00\n",
      " 3.20000000e+01 1.12000000e+02 0.00000000e+00 2.00000000e+00\n",
      " 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00\n",
      " 0.00000000e+00 3.30000000e+01 4.24233531e-01] tensor(7776.9434)\n",
      "[ 12.         843.           0.           1.          42.\n",
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      "   0.           0.           0.          31.           0.93187116] tensor(9107.9121)\n",
      "[ 2.00000000e+00  9.44000000e+02  0.00000000e+00  1.00000000e+00\n",
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      "  0.00000000e+00  2.00000000e+01 -8.85032618e-01] tensor(5184.6289)\n",
      "[  1.         635.           0.           1.          21.\n",
      " 110.           0.           2.           0.           0.\n",
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      "[  2.      159.        1.        1.       42.       86.        0.\n",
      "   0.        0.        0.        0.        0.        0.       31.\n",
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      "[  2.         734.           1.           1.          42.\n",
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      "[  2.          26.           0.           1.          31.\n",
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      "[  1.         543.           0.           1.          31.\n",
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      "[  1.         151.           0.           1.          32.\n",
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      "   4.           0.           3.          33.          -1.29818526] tensor(4268.)\n",
      "[  2.         844.           0.           1.          42.\n",
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      "[ 2.00000000e+00  1.23300000e+03  0.00000000e+00  0.00000000e+00\n",
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      "[  2.         635.           0.           1.          42.\n",
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      "[  1.        554.          1.          1.         40.        120.\n",
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      "[ 12.         159.           1.           1.          22.\n",
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      "[ 1.00000000e+00  1.70300000e+03  0.00000000e+00  0.00000000e+00\n",
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      "  0.00000000e+00  3.30000000e+01 -4.59278471e-01] tensor(6000.)\n",
      "[ 1.00000000e+00  7.34000000e+02  1.00000000e+00  1.00000000e+00\n",
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      " 0.00000000e+00 2.20000000e+01 2.00470543e-01] tensor(7288.6064)\n",
      "[ 1.00000000e+00  9.44000000e+02  0.00000000e+00  1.00000000e+00\n",
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      "[ 2.00000000e+00  1.70300000e+03  0.00000000e+00  0.00000000e+00\n",
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     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[2.00000000e+00 9.44000000e+02 0.00000000e+00 1.00000000e+00\n",
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      "[  1.         840.           0.           1.          40.\n",
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      "[  2.         489.           0.           1.          23.\n",
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      "[ 12.         424.           0.           1.          39.\n",
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      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  2.60000000e+01 -2.46441106e-01] tensor(6402.)\n",
      "[  1.         836.           0.           1.          34.\n",
      " 117.           0.           2.           0.           0.\n",
      "   0.           0.           0.          26.           1.82760652] tensor(15000.)\n",
      "[  1.         837.           0.           1.          28.\n",
      " 112.           0.           2.           0.           0.\n",
      "   0.           0.           0.          33.          -1.29818526] tensor(4268.)\n",
      "[1.00000000e+00 1.70300000e+03 0.00000000e+00 0.00000000e+00\n",
      " 4.20000000e+01 8.60000000e+01 0.00000000e+00 0.00000000e+00\n",
      " 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00\n",
      " 0.00000000e+00 3.10000000e+01 1.84178959e+00] tensor(15301.5059)\n",
      "[ 2.00000000e+00  1.44700000e+03  0.00000000e+00  1.00000000e+00\n",
      "  3.20000000e+01  1.05000000e+02  1.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  3.10000000e+01 -1.18132525e+00] tensor(4553.9561)\n",
      "[  2.         554.           1.           1.          42.\n",
      "  86.           0.           0.           0.           0.\n",
      "   0.           0.           0.          31.           1.47629237] tensor(11384.8896)\n",
      "[ 2.00000000e+00  1.70300000e+03  0.00000000e+00  0.00000000e+00\n",
      "  3.60000000e+01  1.14000000e+02  1.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  1.90000000e+01 -1.04358761e+00] tensor(4859.0713)\n",
      "[2.00000000e+00 1.70300000e+03 0.00000000e+00 0.00000000e+00\n",
      " 3.70000000e+01 1.21000000e+02 1.00000000e+00 0.00000000e+00\n",
      " 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00\n",
      " 0.00000000e+00 3.30000000e+01 1.81503227e+00] tensor(14756.6074)\n",
      "[  2.          10.           0.           1.          30.\n",
      " 103.           1.           0.           0.           0.\n",
      "   0.           0.           0.          33.           1.95140677] tensor(20744.9961)\n",
      "[  1.         852.           0.           1.          30.\n",
      " 114.           0.           2.           3.           3.\n",
      "   0.           0.           0.          30.           1.75628398] tensor(13829.9971)\n",
      "[ 2.00000000e+00  1.70300000e+03  0.00000000e+00  0.00000000e+00\n",
      "  4.20000000e+01  8.60000000e+01  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  2.90000000e+01 -8.13051736e-02] tensor(6720.0938)\n",
      "[ 1.00000000e+00  6.52000000e+02  0.00000000e+00  1.00000000e+00\n",
      "  4.10000000e+01  1.25000000e+02  0.00000000e+00  2.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  3.10000000e+01 -3.01143857e-01] tensor(6298.1201)\n",
      "[  1.         257.           1.           1.          37.\n",
      " 112.           0.           2.           0.           0.\n",
      "   0.           0.           0.          33.           0.93187116] tensor(9107.9121)\n",
      "[ 2.00000000e+00  9.44000000e+02  0.00000000e+00  1.00000000e+00\n",
      "  3.40000000e+01  1.14000000e+02  1.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  3.10000000e+01 -2.48496109e-02] tensor(6830.9341)\n",
      "[  2.         160.           1.           1.          42.\n",
      "  86.           0.           0.           0.           0.\n",
      "   0.           0.           0.          30.          -1.18132525] tensor(4553.9561)\n",
      "[2.00000000e+00 1.70300000e+03 0.00000000e+00 0.00000000e+00\n",
      " 4.20000000e+01 8.60000000e+01 0.00000000e+00 0.00000000e+00\n",
      " 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00\n",
      " 0.00000000e+00 3.00000000e+01 6.41262404e-01] tensor(8297.9980)\n",
      "[ 2.00000000e+00  1.70300000e+03  0.00000000e+00  0.00000000e+00\n",
      "  3.10000000e+01  1.17000000e+02  1.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  2.90000000e+01 -1.04358761e+00] tensor(4859.0713)\n",
      "[  1.        837.          0.          1.         34.        112.\n",
      "   0.          2.          0.          0.          0.          0.\n",
      "   0.         30.          1.2775747] tensor(10369.2578)\n",
      "[2.00000000e+00 4.07000000e+02 1.00000000e+00 1.00000000e+00\n",
      " 2.80000000e+01 1.16000000e+02 1.00000000e+00 0.00000000e+00\n",
      " 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00\n",
      " 0.00000000e+00 3.30000000e+01 2.00470543e-01] tensor(7288.6064)\n",
      "[  1.         159.           1.           1.          39.\n",
      " 121.           0.           2.           0.           0.\n",
      "   0.           0.           0.          28.           1.16739401] tensor(9916.5791)\n",
      "[ 2.00000000e+00  1.62900000e+03  0.00000000e+00  0.00000000e+00\n",
      "  3.40000000e+01  1.08000000e+02  0.00000000e+00  2.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  3.30000000e+01 -8.13051736e-02] tensor(6720.0938)\n",
      "[1.00000000e+00 8.47000000e+02 0.00000000e+00 1.00000000e+00\n",
      " 3.40000000e+01 1.13000000e+02 0.00000000e+00 2.00000000e+00\n",
      " 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00\n",
      " 0.00000000e+00 3.10000000e+01 2.00470543e-01] tensor(7288.6064)\n",
      "[ 2.00000000e+00  2.60000000e+02  0.00000000e+00  1.00000000e+00\n",
      "  3.00000000e+01  1.14000000e+02  1.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  1.70000000e+01 -2.46441106e-01] tensor(6402.)\n",
      "[ 2.00000000e+00  1.70300000e+03  0.00000000e+00  0.00000000e+00\n",
      "  2.50000000e+01  1.17000000e+02  1.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  2.10000000e+01 -5.11043371e-01] tensor(5902.6431)\n",
      "[ 2.00000000e+00  7.12000000e+02  0.00000000e+00  1.00000000e+00\n",
      "  3.00000000e+01  1.20000000e+02  1.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  2.40000000e+01 -5.11043371e-01] tensor(5902.6431)\n",
      "[  1.         406.           0.           1.          24.\n",
      " 118.           0.           2.           0.           0.\n",
      "   0.           0.           0.          31.          -1.18132525] tensor(4553.9561)\n",
      "[  1.         160.           1.           1.          29.\n",
      " 105.           0.           2.           0.           0.\n",
      "   0.           0.           0.          33.          -1.29818526] tensor(4268.)\n",
      "[ 2.00000000e+00  8.51000000e+02  0.00000000e+00  1.00000000e+00\n",
      "  3.00000000e+01  1.14000000e+02  1.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  3.00000000e+01 -2.46441106e-01] tensor(6402.)\n",
      "[ 1.00000000e+00  1.70300000e+03  0.00000000e+00  0.00000000e+00\n",
      "  2.80000000e+01  1.04000000e+02  0.00000000e+00  2.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  3.30000000e+01 -4.59278471e-01] tensor(6000.)\n",
      "[  1.          45.           0.           1.          27.\n",
      " 112.           0.           2.           0.           0.\n",
      "   0.           0.           0.          30.           0.93187116] tensor(9107.9121)\n",
      "[  2.         851.           0.           1.          42.\n",
      "  86.           0.           0.           0.           0.\n",
      "   0.           0.           0.          25.          -1.18132525] tensor(4553.9561)\n",
      "[ 1.00000000e+00  1.70300000e+03  0.00000000e+00  0.00000000e+00\n",
      "  3.40000000e+01  1.08000000e+02  0.00000000e+00  2.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  3.30000000e+01 -1.04358761e+00] tensor(4859.0713)\n",
      "[  1.         772.           0.           1.          31.\n",
      " 118.           0.           2.           0.           0.\n",
      "   0.           0.           0.          26.          -1.18132525] tensor(4553.9561)\n",
      "[  2.          10.           0.           1.          36.\n",
      " 103.           1.           0.           0.           0.\n",
      "   0.           0.           0.          33.          -1.18132525] tensor(4553.9561)\n",
      "[  2.        159.          1.          1.         42.         86.\n",
      "   0.          0.          0.          0.          0.          0.\n",
      "   0.         29.          0.6412624] tensor(8297.9980)\n",
      "[  1.         407.           1.           1.          38.\n",
      " 115.           0.           2.           0.           0.\n",
      "   0.           0.           0.          31.           1.58881165] tensor(12147.6777)\n",
      "[ 2.00000000e+00  7.55000000e+02  0.00000000e+00  1.00000000e+00\n",
      "  3.10000000e+01  1.17000000e+02  1.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  3.00000000e+01 -3.01143857e-01] tensor(6298.1201)\n",
      "[  2.         882.           0.           0.          38.\n",
      " 115.           0.           2.           0.           0.\n",
      "   0.           0.           0.          31.          -0.88503262] tensor(5184.6289)\n",
      "[ 2.00000000e+00  1.19100000e+03  0.00000000e+00  0.00000000e+00\n",
      "  3.50000000e+01  1.18000000e+02  1.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  3.30000000e+01 -8.85032618e-01] tensor(5184.6289)\n",
      "[1.00000000e+00 7.34000000e+02 1.00000000e+00 1.00000000e+00\n",
      " 3.80000000e+01 1.21000000e+02 0.00000000e+00 2.00000000e+00\n",
      " 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00\n",
      " 0.00000000e+00 3.10000000e+01 7.32566829e-01] tensor(8536.)\n",
      "[ 2.00000000e+00  4.07000000e+02  1.00000000e+00  1.00000000e+00\n",
      "  2.80000000e+01  1.13000000e+02  1.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  3.30000000e+01 -3.01143857e-01] tensor(6298.1201)\n",
      "[ 1.00000000e+00  8.40000000e+02  0.00000000e+00  1.00000000e+00\n",
      "  2.90000000e+01  1.11000000e+02  0.00000000e+00  2.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  3.30000000e+01 -2.48496109e-02] tensor(6830.9341)\n",
      "[  2.         197.           0.           1.          21.\n",
      " 111.           1.           0.           0.           0.\n",
      "   0.           0.           0.          30.          -0.88503262] tensor(5184.6289)\n",
      "[  1.         714.           0.           1.          30.\n",
      " 103.           0.           2.           0.           0.\n",
      "   0.           0.           0.          27.          -0.88503262] tensor(5184.6289)\n",
      "[  1.           9.           0.           1.          34.\n",
      " 108.           0.           2.           0.           0.\n",
      "   0.           0.           0.          31.          -0.88503262] tensor(5184.6289)\n",
      "[2.00000000e+00 7.53000000e+02 0.00000000e+00 1.00000000e+00\n",
      " 4.20000000e+01 8.60000000e+01 0.00000000e+00 0.00000000e+00\n",
      " 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00\n",
      " 0.00000000e+00 3.30000000e+01 3.68223674e-01] tensor(7650.7529)\n",
      "[  2.         407.           1.           1.          35.\n",
      " 114.           1.           0.           0.           0.\n",
      "   0.           0.           0.          33.          -1.04358761] tensor(4859.0713)\n",
      "[ 1.20000000e+01  9.00000000e+00  0.00000000e+00  1.00000000e+00\n",
      "  3.90000000e+01  1.16000000e+02  0.00000000e+00  2.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  3.10000000e+01 -8.13051736e-02] tensor(6720.0938)\n",
      "[  1.         649.           0.           1.          38.\n",
      " 114.           0.           2.           0.           0.\n",
      "   0.           0.           0.          33.          -1.04358761] tensor(4859.0713)\n",
      "[ 2.00000000e+00  1.19900000e+03  0.00000000e+00  1.00000000e+00\n",
      "  3.10000000e+01  1.04000000e+02  0.00000000e+00  2.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  3.10000000e+01 -2.46441106e-01] tensor(6402.)\n",
      "[2.00000000e+00 1.63000000e+03 0.00000000e+00 0.00000000e+00\n",
      " 3.40000000e+01 1.13000000e+02 1.00000000e+00 0.00000000e+00\n",
      " 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00\n",
      " 0.00000000e+00 3.30000000e+01 9.31871161e-01] tensor(9107.9121)\n",
      "[ 1.00000000e+00  4.07000000e+02  1.00000000e+00  1.00000000e+00\n",
      "  4.20000000e+01  8.60000000e+01  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  3.30000000e+01 -2.48496109e-02] tensor(6830.9341)\n",
      "[  1.         311.           0.           1.          28.\n",
      " 115.           0.           2.           3.           3.\n",
      "   0.           0.           0.          31.           1.68158211] tensor(12961.5723)\n",
      "[  1.         730.           0.           1.          26.\n",
      " 112.           0.           2.           0.           0.\n",
      "   0.           0.           0.          33.           0.84684595] tensor(8853.9639)\n",
      "[ 12.         840.           0.           1.          42.\n",
      "  86.           0.           0.           0.           0.\n",
      "   0.           0.           0.          22.          -1.18132525] tensor(4553.9561)\n",
      "[ 1.00000000e+00  1.70300000e+03  0.00000000e+00  0.00000000e+00\n",
      "  3.10000000e+01  1.18000000e+02  0.00000000e+00  2.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  3.30000000e+01 -5.11043371e-01] tensor(5902.6431)\n",
      "[  1.         160.           1.           1.          42.\n",
      "  86.           0.           0.           0.           0.\n",
      "   0.           0.           0.          33.           0.20047054] tensor(7288.6064)\n",
      "[  1.         257.           1.           1.          39.\n",
      " 117.           0.           2.           0.           0.\n",
      "   0.           0.           0.          30.          -0.51104337] tensor(5902.6431)\n",
      "[  1.          49.           0.           1.          41.\n",
      " 123.           0.           2.           0.           0.\n",
      "   0.           0.           0.          30.           0.20047054] tensor(7288.6064)\n",
      "[ 2.00000000e+00  1.70300000e+03  0.00000000e+00  0.00000000e+00\n",
      "  3.40000000e+01  1.15000000e+02  1.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  3.30000000e+01 -1.18132525e+00] tensor(4553.9561)\n",
      "[  1.         748.           0.           1.          34.\n",
      " 108.           0.           2.           0.           0.\n",
      "   0.           0.           0.          33.          -1.04358761] tensor(4859.0713)\n",
      "[ 12.         841.           0.           1.          41.\n",
      " 123.           0.           2.           0.           0.\n",
      "   0.           0.           0.          31.          -0.88503262] tensor(5184.6289)\n",
      "[2.00000000e+00 1.70300000e+03 0.00000000e+00 0.00000000e+00\n",
      " 3.80000000e+01 1.21000000e+02 1.00000000e+00 0.00000000e+00\n",
      " 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00\n",
      " 0.00000000e+00 2.40000000e+01 7.32566829e-01] tensor(8536.)\n",
      "[ 3.00000000e+00  1.70300000e+03  0.00000000e+00  0.00000000e+00\n",
      "  3.00000000e+01  1.14000000e+02  1.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  3.30000000e+01 -4.59278471e-01] tensor(6000.)\n",
      "[  1.         635.           0.           1.          35.\n",
      " 118.           0.           2.           0.           0.\n",
      "   0.           0.           0.          31.          -1.04358761] tensor(4859.0713)\n",
      "[ 2.00000000e+00  9.00000000e+00  0.00000000e+00  1.00000000e+00\n",
      "  3.00000000e+01  1.14000000e+02  1.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  2.10000000e+01 -8.13051736e-02] tensor(6720.0938)\n",
      "[  1.         753.           0.           1.          30.\n",
      " 114.           0.           2.           0.           0.\n",
      "   0.           0.           0.          33.           1.86966682] tensor(16005.)\n",
      "[  3.        840.          0.          1.         37.        114.\n",
      "   0.          2.          0.          0.          0.          0.\n",
      "   0.         31.          1.2775747] tensor(10369.2578)\n",
      "[  2.         162.           0.           1.          33.\n",
      " 120.           1.           0.           0.           0.\n",
      "   0.           0.           0.          33.          -1.18132525] tensor(4553.9561)\n",
      "[  1.          10.           0.           1.          31.\n",
      " 120.           0.           2.           3.           3.\n",
      "   0.           0.           0.          33.           1.11436842] tensor(9718.1426)\n",
      "[  2.         160.           1.           1.          30.\n",
      " 103.           1.           0.           0.           0.\n",
      "   0.           0.           0.          33.          -1.39501774] tensor(4000.)\n",
      "[  1.         944.           0.           1.          37.\n",
      " 121.           0.           2.           0.           0.\n",
      "   0.           0.           0.          31.          -1.29818526] tensor(4268.)\n",
      "[  2.          54.           0.           1.          31.\n",
      " 117.           0.           2.           0.           0.\n",
      "   0.           0.           0.          20.          -0.45927847] tensor(6000.)\n",
      "[ 1.00000000e+00  5.54000000e+02  1.00000000e+00  1.00000000e+00\n",
      "  3.10000000e+01  1.18000000e+02  0.00000000e+00  2.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  3.30000000e+01 -5.11043371e-01] tensor(5902.6431)\n",
      "[1.00000000e+00 7.18000000e+02 0.00000000e+00 1.00000000e+00\n",
      " 3.40000000e+01 1.08000000e+02 0.00000000e+00 2.00000000e+00\n",
      " 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00\n",
      " 0.00000000e+00 3.30000000e+01 2.00470543e-01] tensor(7288.6064)\n",
      "[1.00000000e+00 6.52000000e+02 0.00000000e+00 1.00000000e+00\n",
      " 4.20000000e+01 8.60000000e+01 0.00000000e+00 0.00000000e+00\n",
      " 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00\n",
      " 0.00000000e+00 3.30000000e+01 2.00470543e-01] tensor(7288.6064)\n",
      "[  2.         151.           0.           1.          42.\n",
      "  86.           0.           0.           0.           0.\n",
      "   0.           0.           0.          33.           1.84178959] tensor(15301.5059)\n",
      "[ 2.00000000e+00  7.47000000e+02  0.00000000e+00  1.00000000e+00\n",
      "  3.50000000e+01  1.19000000e+02  1.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  3.30000000e+01 -5.11043371e-01] tensor(5902.6431)\n",
      "[1.00000000e+00 1.70300000e+03 0.00000000e+00 0.00000000e+00\n",
      " 3.10000000e+01 1.21000000e+02 0.00000000e+00 2.00000000e+00\n",
      " 3.00000000e+00 3.00000000e+00 0.00000000e+00 0.00000000e+00\n",
      " 0.00000000e+00 3.10000000e+01 1.82760652e+00] tensor(15000.)\n",
      "[  1.         159.           1.           1.          24.\n",
      " 116.           0.           2.           0.           0.\n",
      "   0.           0.           0.          30.          -0.70677457] tensor(5531.9990)\n",
      "[ 4.00000000e+00  1.70300000e+03  0.00000000e+00  0.00000000e+00\n",
      "  4.20000000e+01  8.60000000e+01  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  3.10000000e+01 -7.06774568e-01] tensor(5531.9990)\n",
      "[2.0000000e+00 8.4000000e+02 0.0000000e+00 1.0000000e+00 2.5000000e+01\n",
      " 1.1300000e+02 0.0000000e+00 2.0000000e+00 0.0000000e+00 0.0000000e+00\n",
      " 0.0000000e+00 0.0000000e+00 0.0000000e+00 3.3000000e+01 5.1998844e-01] tensor(8000.)\n",
      "[  1.         159.           1.           1.          35.\n",
      " 118.           0.           2.           0.           0.\n",
      "   0.           0.           0.          33.          -1.18132525] tensor(4553.9561)\n",
      "[  2.         311.           0.           1.          38.\n",
      " 115.           0.           2.           0.           0.\n",
      "   0.           0.           0.          33.           0.42423353] tensor(7776.9434)\n",
      "[  1.         159.           1.           1.          39.\n",
      " 116.           0.           2.           3.           3.\n",
      "   0.           0.           3.          33.           1.58881165] tensor(12147.6777)\n",
      "[  1.         178.           0.           1.          43.\n",
      " 125.           0.           2.           0.           0.\n",
      "   0.           0.           0.          33.          -1.29818526] tensor(4268.)\n",
      "[  1.         407.           1.           1.          27.\n",
      " 110.           0.           2.           0.           0.\n",
      "   0.           0.           0.          30.          -1.18132525] tensor(4553.9561)\n",
      "[  1.      160.        1.        1.       45.      126.        0.\n",
      "   2.        0.        0.        0.        0.        0.       33.\n",
      "   0.58742] tensor(8163.3535)\n",
      "[ 1.          9.          0.          1.         42.         86.\n",
      "  0.          0.          0.          0.          0.          0.\n",
      "  0.         31.         -1.04358761] tensor(4859.0713)\n",
      "[ 2.00000000e+00  8.56000000e+02  0.00000000e+00  1.00000000e+00\n",
      "  3.60000000e+01  1.17000000e+02  0.00000000e+00  2.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  2.80000000e+01 -7.06774568e-01] tensor(5531.9990)\n",
      "[  1.         865.           0.           1.          34.\n",
      " 115.           0.           2.           0.           0.\n",
      "   0.           0.           0.          33.          -1.39501774] tensor(4000.)\n",
      "[ 1.00000000e+00  7.18000000e+02  0.00000000e+00  1.00000000e+00\n",
      "  3.90000000e+01  1.17000000e+02  0.00000000e+00  2.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  2.20000000e+01 -3.01143857e-01] tensor(6298.1201)\n",
      "[  1.         159.           1.           1.          26.\n",
      " 101.           0.           2.           0.           0.\n",
      "   0.           0.           0.          27.          -1.04358761] tensor(4859.0713)\n",
      "[  1.         160.           1.           1.          36.\n",
      " 117.           0.           2.           0.           0.\n",
      "   0.           0.           0.          23.          -0.88503262] tensor(5184.6289)\n",
      "[  1.         160.           1.           1.          39.\n",
      " 116.           0.           2.           3.           3.\n",
      "   0.           0.           3.          31.           1.42012124] tensor(11063.9980)\n",
      "[  3.         734.           1.           1.          41.\n",
      " 123.           1.           0.           0.           0.\n",
      "   0.           0.           0.          33.           1.34300582] tensor(10670.)\n",
      "[  1.         840.           0.           1.          28.\n",
      " 115.           0.           2.           0.           0.\n",
      "   0.           0.           0.          23.           1.18880493] tensor(10000.)\n",
      "[  1.         407.           1.           1.          28.\n",
      " 115.           0.           2.           0.           0.\n",
      "   0.           0.           0.          30.          -0.88503262] tensor(5184.6289)\n",
      "[  2.         235.           0.           1.          43.\n",
      " 126.           1.           0.           0.           0.\n",
      "   0.           0.           0.          33.          -1.04358761] tensor(4859.0713)\n",
      "[  2.         200.           0.           1.          39.\n",
      " 116.           0.           2.           3.           0.\n",
      "   0.           0.           0.          31.          -0.24644111] tensor(6402.)\n",
      "[  1.         230.           0.           1.          23.\n",
      " 113.           0.           2.           0.           0.\n",
      "   0.           0.           0.          31.          -0.88503262] tensor(5184.6289)\n",
      "[2.00000000e+00 1.70300000e+03 0.00000000e+00 0.00000000e+00\n",
      " 4.20000000e+01 8.60000000e+01 0.00000000e+00 0.00000000e+00\n",
      " 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00\n",
      " 0.00000000e+00 3.30000000e+01 7.32566829e-01] tensor(8536.)\n",
      "[  1.         736.           0.           1.          31.\n",
      " 117.           0.           2.           3.           3.\n",
      "   0.           0.           0.          30.           1.36054634] tensor(10755.5107)\n",
      "[  1.         734.           1.           1.          32.\n",
      " 112.           0.           2.           0.           0.\n",
      "   0.           0.           0.          30.          -0.88503262] tensor(5184.6289)\n",
      "[ 2.00000000e+00  7.53000000e+02  0.00000000e+00  1.00000000e+00\n",
      "  4.50000000e+01  1.26000000e+02  1.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  3.10000000e+01 -2.46441106e-01] tensor(6402.)\n",
      "[1.00000000e+00 1.70300000e+03 0.00000000e+00 0.00000000e+00\n",
      " 2.10000000e+01 1.10000000e+02 0.00000000e+00 2.00000000e+00\n",
      " 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00\n",
      " 0.00000000e+00 3.30000000e+01 1.32425521e+00] tensor(10580.9893)\n",
      "[ 1.00000000e+00  3.11000000e+02  0.00000000e+00  1.00000000e+00\n",
      "  4.20000000e+01  8.60000000e+01  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  1.80000000e+01 -2.46441106e-01] tensor(6402.)\n",
      "[ 2.00000000e+00  1.70300000e+03  0.00000000e+00  0.00000000e+00\n",
      "  4.20000000e+01  8.60000000e+01  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  2.60000000e+01 -2.48496109e-02] tensor(6830.9341)\n",
      "[ 2.00000000e+00  8.41000000e+02  0.00000000e+00  1.00000000e+00\n",
      "  2.30000000e+01  1.13000000e+02  1.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  3.10000000e+01 -7.06774568e-01] tensor(5531.9990)\n",
      "[1.00000000e+00 6.58000000e+02 0.00000000e+00 1.00000000e+00\n",
      " 2.80000000e+01 1.12000000e+02 0.00000000e+00 2.00000000e+00\n",
      " 3.00000000e+00 3.00000000e+00 0.00000000e+00 0.00000000e+00\n",
      " 3.00000000e+00 2.70000000e+01 6.41262404e-01] tensor(8297.9980)\n",
      "[1.20000000e+01 3.11000000e+02 0.00000000e+00 1.00000000e+00\n",
      " 4.30000000e+01 8.70000000e+01 0.00000000e+00 2.00000000e+00\n",
      " 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00\n",
      " 0.00000000e+00 3.30000000e+01 1.43569229e-01] tensor(7170.3403)\n",
      "[2.00000000e+00 1.70300000e+03 0.00000000e+00 0.00000000e+00\n",
      " 3.70000000e+01 1.12000000e+02 0.00000000e+00 2.00000000e+00\n",
      " 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00\n",
      " 0.00000000e+00 3.30000000e+01 6.41262404e-01] tensor(8297.9980)\n",
      "[  1.         257.           1.           1.          31.\n",
      " 121.           0.           2.           0.           0.\n",
      "   0.           0.           0.          29.           0.93187116] tensor(9107.9121)\n",
      "[2.00000000e+00 5.30000000e+02 0.00000000e+00 1.00000000e+00\n",
      " 4.20000000e+01 8.60000000e+01 0.00000000e+00 0.00000000e+00\n",
      " 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00\n",
      " 0.00000000e+00 3.10000000e+01 3.68223674e-01] tensor(7650.7529)\n",
      "[ 2.00000000e+00  7.34000000e+02  1.00000000e+00  1.00000000e+00\n",
      "  3.40000000e+01  1.08000000e+02  1.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  2.40000000e+01 -7.06774568e-01] tensor(5531.9990)\n",
      "[  1.           9.           0.           1.          30.\n",
      " 114.           0.           2.           0.           0.\n",
      "   0.           0.           0.          31.          -0.88503262] tensor(5184.6289)\n",
      "[ 1.00000000e+00  1.70300000e+03  0.00000000e+00  0.00000000e+00\n",
      "  4.20000000e+01  8.60000000e+01  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  2.50000000e+01 -8.85032618e-01] tensor(5184.6289)\n",
      "[  1.         841.           0.           1.          27.\n",
      " 114.           0.           2.           0.           0.\n",
      "   0.           0.           0.          14.           1.58881165] tensor(12147.6777)\n",
      "[  2.         311.           0.           1.          36.\n",
      " 117.           0.           2.           0.           0.\n",
      "   0.           0.           0.          23.           0.42423353] tensor(7776.9434)\n",
      "[  1.         649.           0.           1.          30.\n",
      " 114.           0.           2.           3.           3.\n",
      "   0.           0.           3.          29.           1.11436842] tensor(9718.1426)\n",
      "[  1.         407.           1.           1.          34.\n",
      " 108.           0.           2.           0.           0.\n",
      "   0.           0.           0.          29.          -1.39501774] tensor(4000.)\n",
      "[ 2.          9.          0.          1.         42.         86.\n",
      "  0.          0.          0.          0.          0.          0.\n",
      "  0.         31.         -0.24644111] tensor(6402.)\n",
      "[ 2.00000000e+00  1.70300000e+03  0.00000000e+00  0.00000000e+00\n",
      "  3.40000000e+01  1.08000000e+02  1.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  3.30000000e+01 -2.48496109e-02] tensor(6830.9341)\n",
      "[  2.         747.           0.           1.          29.\n",
      " 116.           0.           2.           0.           0.\n",
      "   0.           0.           0.          33.          -0.88503262] tensor(5184.6289)\n",
      "[  1.         851.           0.           1.          38.\n",
      " 114.           0.           2.           0.           0.\n",
      "   0.           0.           0.          33.          -0.88503262] tensor(5184.6289)\n",
      "[ 2.00000000e+00  8.39000000e+02  0.00000000e+00  1.00000000e+00\n",
      "  3.20000000e+01  1.18000000e+02  1.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  3.10000000e+01 -2.46441106e-01] tensor(6402.)\n",
      "[ 2.00000000e+00  7.18000000e+02  0.00000000e+00  1.00000000e+00\n",
      "  3.40000000e+01  1.13000000e+02  0.00000000e+00  2.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  3.10000000e+01 -3.01143857e-01] tensor(6298.1201)\n",
      "[ 2.00000000e+00  1.19100000e+03  0.00000000e+00  0.00000000e+00\n",
      "  3.10000000e+01  1.04000000e+02  1.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  2.70000000e+01 -8.85032618e-01] tensor(5184.6289)\n",
      "[1.00000000e+00 6.52000000e+02 0.00000000e+00 1.00000000e+00\n",
      " 4.20000000e+01 8.60000000e+01 0.00000000e+00 0.00000000e+00\n",
      " 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00\n",
      " 0.00000000e+00 2.90000000e+01 4.24233531e-01] tensor(7776.9434)\n",
      "[  1.         753.           0.           1.          26.\n",
      " 101.           0.           2.           0.           0.\n",
      "   0.           0.           0.          15.          -1.04358761] tensor(4859.0713)\n",
      "[ 1.00000000e+00  1.70300000e+03  0.00000000e+00  0.00000000e+00\n",
      "  3.40000000e+01  1.08000000e+02  0.00000000e+00  2.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  3.10000000e+01 -2.46441106e-01] tensor(6402.)\n",
      "[2.0000000e+00 1.7030000e+03 0.0000000e+00 0.0000000e+00 3.2000000e+01\n",
      " 1.1900000e+02 1.0000000e+00 0.0000000e+00 0.0000000e+00 0.0000000e+00\n",
      " 0.0000000e+00 0.0000000e+00 0.0000000e+00 3.3000000e+01 5.1998844e-01] tensor(8000.)\n",
      "[  1.         159.           1.           1.          32.\n",
      " 118.           0.           2.           3.           3.\n",
      "   0.           0.           0.          23.          -0.51104337] tensor(5902.6431)\n",
      "[ 2.00000000e+00  9.44000000e+02  0.00000000e+00  1.00000000e+00\n",
      "  4.20000000e+01  8.60000000e+01  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  1.90000000e+01 -3.01143857e-01] tensor(6298.1201)\n",
      "[2.00000000e+00 1.70300000e+03 0.00000000e+00 0.00000000e+00\n",
      " 3.60000000e+01 1.17000000e+02 1.00000000e+00 0.00000000e+00\n",
      " 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00\n",
      " 0.00000000e+00 3.10000000e+01 2.00470543e-01] tensor(7288.6064)\n",
      "[ 2.00000000e+00  8.40000000e+02  0.00000000e+00  1.00000000e+00\n",
      "  3.00000000e+01  1.17000000e+02  1.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  3.30000000e+01 -4.59278471e-01] tensor(6000.)\n",
      "[  1.         159.           1.           1.          39.\n",
      " 116.           0.           2.           0.           0.\n",
      "   0.           0.           0.          31.           1.94012006] tensor(19442.3574)\n",
      "[2.0000000e+00 1.7030000e+03 0.0000000e+00 0.0000000e+00 4.3000000e+01\n",
      " 1.2400000e+02 1.0000000e+00 0.0000000e+00 0.0000000e+00 0.0000000e+00\n",
      " 0.0000000e+00 0.0000000e+00 0.0000000e+00 3.3000000e+01 5.1998844e-01] tensor(8000.)\n",
      "[  2.         734.           1.           1.          31.\n",
      " 117.           1.           0.           0.           0.\n",
      "   0.           0.           0.          33.          -1.29818526] tensor(4268.)\n",
      "[  1.         407.           1.           1.          42.\n",
      "  86.           0.           0.           0.           0.\n",
      "   0.           0.           0.          30.           0.42423353] tensor(7776.9434)\n",
      "[ 1.00000000e+00  6.35000000e+02  0.00000000e+00  1.00000000e+00\n",
      "  2.90000000e+01  1.11000000e+02  0.00000000e+00  2.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  3.00000000e+01 -4.59278471e-01] tensor(6000.)\n",
      "[ 2.00000000e+00  5.80000000e+01  0.00000000e+00  1.00000000e+00\n",
      "  3.50000000e+01  1.18000000e+02  1.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  3.30000000e+01 -8.13051736e-02] tensor(6720.0938)\n",
      "[  2.         424.           0.           1.          34.\n",
      " 113.           0.           2.           0.           0.\n",
      "   0.           0.           0.          30.          -1.29818526] tensor(4268.)\n",
      "[ 2.00000000e+00  2.80000000e+01  0.00000000e+00  1.00000000e+00\n",
      "  3.00000000e+01  1.04000000e+02  1.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  3.30000000e+01 -8.13051736e-02] tensor(6720.0938)\n",
      "[  2.         160.           1.           1.          42.\n",
      "  86.           0.           0.           0.           0.\n",
      "   0.           0.           0.          33.          -1.04358761] tensor(4859.0713)\n",
      "[ 2.00000000e+00  8.40000000e+02  0.00000000e+00  1.00000000e+00\n",
      "  4.20000000e+01  8.60000000e+01  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  2.80000000e+01 -5.11043371e-01] tensor(5902.6431)\n",
      "[  1.         554.           1.           1.          30.\n",
      " 114.           0.           2.           0.           0.\n",
      "   0.           0.           0.          25.          -1.18132525] tensor(4553.9561)\n",
      "[ 2.00000000e+00  1.70300000e+03  0.00000000e+00  0.00000000e+00\n",
      "  2.80000000e+01  1.13000000e+02  1.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  3.10000000e+01 -2.46441106e-01] tensor(6402.)\n",
      "[  1.         652.           0.           1.          34.\n",
      " 108.           0.           2.           0.           0.\n",
      "   0.           0.           0.          33.           0.73256683] tensor(8536.)\n",
      "[1.00000000e+00 4.89000000e+02 0.00000000e+00 1.00000000e+00\n",
      " 3.10000000e+01 1.17000000e+02 0.00000000e+00 2.00000000e+00\n",
      " 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00\n",
      " 0.00000000e+00 2.00000000e+01 1.43569229e-01] tensor(7170.3403)\n",
      "[ 1.00000000e+00  6.49000000e+02  0.00000000e+00  1.00000000e+00\n",
      "  2.80000000e+01  1.04000000e+02  0.00000000e+00  2.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  3.00000000e+01 -8.13051736e-02] tensor(6720.0938)\n",
      "[ 2.00000000e+00  3.48000000e+02  0.00000000e+00  1.00000000e+00\n",
      "  3.40000000e+01  1.08000000e+02  0.00000000e+00  2.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  3.30000000e+01 -3.01143857e-01] tensor(6298.1201)\n",
      "[  6.         734.           1.           1.          42.\n",
      "  86.           0.           0.           0.           0.\n",
      "   0.           0.           0.          33.          -1.18132525] tensor(4553.9561)\n",
      "[ 1.00000000e+00  6.52000000e+02  0.00000000e+00  1.00000000e+00\n",
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      "[1.00000000e+00 4.07000000e+02 1.00000000e+00 1.00000000e+00\n",
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      " 0.00000000e+00 3.00000000e+01 3.68223674e-01] tensor(7650.7529)\n",
      "[ 2.00000000e+00  7.34000000e+02  1.00000000e+00  1.00000000e+00\n",
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      "  0.00000000e+00  3.10000000e+01 -8.13051736e-02] tensor(6720.0938)\n",
      "[ 1.00000000e+00  9.44000000e+02  0.00000000e+00  1.00000000e+00\n",
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      "  0.00000000e+00  3.00000000e+01 -3.01143857e-01] tensor(6298.1201)\n",
      "[ 2.00000000e+00  1.59000000e+02  1.00000000e+00  1.00000000e+00\n",
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      "  0.00000000e+00  2.00000000e+01 -2.48496109e-02] tensor(6830.9341)\n",
      "[ 2.00000000e+00  9.44000000e+02  0.00000000e+00  1.00000000e+00\n",
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      "  0.00000000e+00  3.00000000e+01 -3.01143857e-01] tensor(6298.1201)\n",
      "[1.00000000e+00 1.70300000e+03 0.00000000e+00 0.00000000e+00\n",
      " 3.00000000e+01 1.20000000e+02 0.00000000e+00 2.00000000e+00\n",
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      " 0.00000000e+00 2.80000000e+01 1.03704191e+00] tensor(9447.1797)\n",
      "[ 2.00000000e+00  7.34000000e+02  1.00000000e+00  1.00000000e+00\n",
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      "  0.00000000e+00  3.30000000e+01 -8.13051736e-02] tensor(6720.0938)\n",
      "[  1.         852.           0.           1.          32.\n",
      " 118.           0.           2.           0.           0.\n",
      "   0.           0.           0.          31.           1.03704191] tensor(9447.1797)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[  1.         754.           0.           1.          39.\n",
      " 116.           0.           2.           3.           3.\n",
      "   0.           0.           3.          31.           1.18880493] tensor(10000.)\n",
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      "  0.00000000e+00  3.30000000e+01 -2.46441106e-01] tensor(6402.)\n",
      "[ 12.         159.           1.           1.          37.\n",
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      "[ 2.          9.          0.          1.         42.         86.\n",
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      "[  2.         311.           0.           1.          30.\n",
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      "[  2.        839.          0.          1.         31.        117.\n",
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      "[  1.         159.           1.           1.          29.\n",
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      "   0.           0.           0.          20.          -1.39501774] tensor(4000.)\n",
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      " 0.00000000e+00 3.30000000e+01 6.41262404e-01] tensor(8297.9980)\n",
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      " 0.00000000e+00 3.30000000e+01 3.68223674e-01] tensor(7650.7529)\n",
      "[  2.         635.           0.           1.          42.\n",
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      "  0.00000000e+00  2.80000000e+01 -2.46441106e-01] tensor(6402.)\n",
      "[  2.         407.           1.           1.          30.\n",
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      " 0.00000000e+00 3.30000000e+01 1.43569229e-01] tensor(7170.3403)\n",
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      "[  2.         424.           0.           1.          33.\n",
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      "[  1.         554.           1.           1.          28.\n",
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      "[  1.         407.           1.           1.          46.\n",
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      "[  1.         407.           1.           1.          34.\n",
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      "[  7.        159.          1.          1.         23.        114.\n",
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      "[ 12.         742.           0.           1.          42.\n",
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      "[ 2.00000000e+00  1.35100000e+03  0.00000000e+00  0.00000000e+00\n",
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      "[ 2.00000000e+00  7.37000000e+02  0.00000000e+00  1.00000000e+00\n",
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      "[ 2.00000000e+00  1.70300000e+03  0.00000000e+00  0.00000000e+00\n",
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      "[  2.         734.           1.           1.          37.\n",
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      "[  3.         734.           1.           1.          42.\n",
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      "[  2.         160.           1.           1.          38.\n",
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      "[  1.         159.           1.           1.          28.\n",
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      "[  1.         230.           0.           1.          34.\n",
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      "[  1.         629.           0.           1.          42.\n",
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      "[ 1.          9.          0.          1.         42.         86.\n",
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      "[  1.         842.           0.           1.          23.\n",
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      " 0.00000000e+00 3.30000000e+01 3.68223674e-01] tensor(7650.7529)\n",
      "[  1.         554.           1.           1.          30.\n",
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      "[  2.         837.           0.           1.          28.\n",
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      "   0.           0.           0.          14.           1.18880493] tensor(10000.)\n",
      "[2.0000000e+00 1.2330000e+03 0.0000000e+00 0.0000000e+00 2.9000000e+01\n",
      " 1.0600000e+02 1.0000000e+00 0.0000000e+00 0.0000000e+00 0.0000000e+00\n",
      " 0.0000000e+00 0.0000000e+00 0.0000000e+00 3.3000000e+01 5.1998844e-01] tensor(8000.)\n",
      "[ 2.00000000e+00  8.51000000e+02  0.00000000e+00  1.00000000e+00\n",
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      "[  2.         407.           1.           1.          35.\n",
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      "[ 1.00000000e+00  7.29000000e+02  0.00000000e+00  1.00000000e+00\n",
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      "[ 2.00000000e+00  8.48000000e+02  0.00000000e+00  1.00000000e+00\n",
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      "[ 1.00000000e+00  8.37000000e+02  0.00000000e+00  1.00000000e+00\n",
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      "[ 2.00000000e+00  1.70300000e+03  0.00000000e+00  0.00000000e+00\n",
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      "  0.00000000e+00  3.30000000e+01 -1.29818526e+00] tensor(4268.)\n",
      "[  2.         159.           1.           1.          42.\n",
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      "[ 4.00000000e+00  1.70300000e+03  0.00000000e+00  0.00000000e+00\n",
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      "[  2.         554.           1.           1.          34.\n",
      " 113.           1.           0.           0.           0.\n",
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      "[  1.         635.           0.           1.          39.\n",
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      "[  1.           9.           0.           1.          30.\n",
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      "[  1.          10.           0.           1.          29.\n",
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      "[ 1.00000000e+00  8.42000000e+02  0.00000000e+00  1.00000000e+00\n",
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      "[  2.         852.           0.           1.          30.\n",
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      "   0.           0.           0.          27.          -1.39501774] tensor(4000.)\n",
      "[  1.         465.           0.           1.          29.\n",
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      "[ 2.00000000e+00  7.55000000e+02  0.00000000e+00  1.00000000e+00\n",
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      "  0.00000000e+00  1.40000000e+01 -2.46441106e-01] tensor(6402.)\n",
      "[ 1.00000000e+00  3.48000000e+02  0.00000000e+00  1.00000000e+00\n",
      "  4.20000000e+01  8.60000000e+01  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  2.60000000e+01 -3.01143857e-01] tensor(6298.1201)\n",
      "[  2.        944.          0.          1.         31.        104.\n",
      "   0.          2.          0.          0.          0.          0.\n",
      "   0.         33.          1.2775747] tensor(10369.2578)\n",
      "[ 1.00000000e+00  7.53000000e+02  0.00000000e+00  1.00000000e+00\n",
      "  4.20000000e+01  8.60000000e+01  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  2.00000000e+01 -7.06774568e-01] tensor(5531.9990)\n",
      "[  2.         754.           0.           1.          34.\n",
      " 108.           1.           0.           0.           0.\n",
      "   0.           0.           0.          11.          -1.04358761] tensor(4859.0713)\n",
      "[2.00000000e+00 1.70300000e+03 0.00000000e+00 0.00000000e+00\n",
      " 2.80000000e+01 1.15000000e+02 0.00000000e+00 2.00000000e+00\n",
      " 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00\n",
      " 0.00000000e+00 3.00000000e+01 3.68223674e-01] tensor(7650.7529)\n",
      "[  2.         159.           1.           1.          29.\n",
      " 111.           1.           0.           0.           0.\n",
      "   0.           0.           0.          30.          -0.45927847] tensor(6000.)\n",
      "[  1.         764.           0.           1.          23.\n",
      " 113.           0.           2.           3.           3.\n",
      "   0.           0.           3.          30.          -1.18132525] tensor(4553.9561)\n",
      "[  1.         160.           1.           1.          42.\n",
      "  86.           0.           0.           0.           0.\n",
      "   0.           0.           0.          31.           0.93187116] tensor(9107.9121)\n",
      "[ 2.00000000e+00  8.52000000e+02  0.00000000e+00  1.00000000e+00\n",
      "  2.30000000e+01  1.13000000e+02  0.00000000e+00  2.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  3.00000000e+01 -8.13051736e-02] tensor(6720.0938)\n",
      "[  2.         852.           0.           1.          42.\n",
      "  86.           0.           0.           0.           0.\n",
      "   0.           0.           0.          30.           1.36054634] tensor(10755.5107)\n",
      "[  1.          58.           0.           1.          36.\n",
      " 113.           0.           2.           0.           0.\n",
      "   0.           0.           0.          31.           1.36054634] tensor(10755.5107)\n",
      "[2.00000000e+00 1.70300000e+03 0.00000000e+00 0.00000000e+00\n",
      " 3.10000000e+01 1.17000000e+02 1.00000000e+00 0.00000000e+00\n",
      " 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00\n",
      " 0.00000000e+00 2.00000000e+01 8.46845955e-01] tensor(8853.9639)\n",
      "[  2.         162.           0.           1.          27.\n",
      " 107.           1.           0.           0.           0.\n",
      "   0.           0.           0.          33.          -1.29818526] tensor(4268.)\n",
      "[  1.        748.          0.          1.         30.        114.\n",
      "   0.          2.          0.          0.          0.          0.\n",
      "   0.         29.          1.9010312] tensor(17077.3359)\n",
      "[ 2.         10.          0.          1.         42.         86.\n",
      "  0.          0.          0.          0.          0.          0.\n",
      "  0.         31.         -0.88503262] tensor(5184.6289)\n",
      "[2.00000000e+00 9.44000000e+02 0.00000000e+00 1.00000000e+00\n",
      " 3.40000000e+01 1.14000000e+02 1.00000000e+00 0.00000000e+00\n",
      " 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00\n",
      " 0.00000000e+00 3.30000000e+01 6.41262404e-01] tensor(8297.9980)\n",
      "[  1.         554.           1.           1.          42.\n",
      "  86.           0.           0.           0.           0.\n",
      "   0.           0.           0.          27.           1.34300582] tensor(10670.)\n",
      "[  1.          10.           0.           1.          29.\n",
      " 105.           0.           2.           0.           0.\n",
      "   0.           0.           0.          33.          -1.39501774] tensor(4000.)\n",
      "[  1.         753.           0.           1.          42.\n",
      "  86.           0.           0.           0.           0.\n",
      "   0.           0.           0.          33.           1.47629237] tensor(11384.8896)\n",
      "[  1.         753.           0.           1.          43.\n",
      " 125.           0.           2.           0.           0.\n",
      "   0.           0.           0.          33.          -1.39501774] tensor(4000.)\n",
      "[ 1.00000000e+00  7.34000000e+02  1.00000000e+00  1.00000000e+00\n",
      "  3.10000000e+01  1.21000000e+02  0.00000000e+00  2.00000000e+00\n",
      "  3.00000000e+00  3.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  2.90000000e+01 -2.46441106e-01] tensor(6402.)\n",
      "[ 1.00000000e+00  1.70300000e+03  0.00000000e+00  0.00000000e+00\n",
      "  3.90000000e+01  1.17000000e+02  0.00000000e+00  2.00000000e+00\n",
      "  3.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  3.10000000e+01 -1.18132525e+00] tensor(4553.9561)\n",
      "[  2.         944.           0.           1.          24.\n",
      " 118.           0.           2.           0.           0.\n",
      "   0.           0.           0.          33.           1.94012006] tensor(19442.3574)\n",
      "[2.00000000e+00 9.44000000e+02 0.00000000e+00 1.00000000e+00\n",
      " 4.20000000e+01 8.60000000e+01 0.00000000e+00 0.00000000e+00\n",
      " 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00\n",
      " 0.00000000e+00 2.60000000e+01 6.41262404e-01] tensor(8297.9980)\n",
      "[ 2.00000000e+00  1.51200000e+03  0.00000000e+00  0.00000000e+00\n",
      "  2.60000000e+01  1.19000000e+02  1.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  2.10000000e+01 -1.39501774e+00] tensor(4000.)\n",
      "[  1.         842.           0.           1.          24.\n",
      " 118.           0.           2.           3.           3.\n",
      "   0.           0.           3.          33.           1.75628398] tensor(13829.9971)\n",
      "[  2.         160.           1.           1.          23.\n",
      " 113.           0.           2.           0.           0.\n",
      "   0.           0.           0.          31.          -1.18132525] tensor(4553.9561)\n",
      "[ 2.00000000e+00  1.70300000e+03  0.00000000e+00  0.00000000e+00\n",
      "  4.10000000e+01  1.23000000e+02  1.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  2.40000000e+01 -1.18132525e+00] tensor(4553.9561)\n",
      "[2.00000000e+00 5.54000000e+02 1.00000000e+00 1.00000000e+00\n",
      " 4.50000000e+01 1.22000000e+02 1.00000000e+00 0.00000000e+00\n",
      " 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00\n",
      " 0.00000000e+00 3.30000000e+01 4.24233531e-01] tensor(7776.9434)\n",
      "[1.00000000e+00 1.70300000e+03 0.00000000e+00 0.00000000e+00\n",
      " 4.20000000e+01 8.60000000e+01 0.00000000e+00 0.00000000e+00\n",
      " 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00\n",
      " 0.00000000e+00 3.30000000e+01 1.95140677e+00] tensor(20744.9961)\n",
      "[  1.         652.           0.           1.          39.\n",
      " 116.           0.           2.           0.           0.\n",
      "   0.           0.           0.          31.           1.86966682] tensor(16005.)\n",
      "[  1.         160.           1.           1.          36.\n",
      " 120.           0.           2.           0.           0.\n",
      "   0.           0.           0.          33.          -1.29818526] tensor(4268.)\n",
      "[  1.         160.           1.           1.          42.\n",
      "  86.           0.           0.           0.           0.\n",
      "   0.           0.           0.          31.          -1.29818526] tensor(4268.)\n",
      "[ 2.00000000e+00  9.00000000e+00  0.00000000e+00  1.00000000e+00\n",
      "  2.60000000e+01  1.19000000e+02  1.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  2.90000000e+01 -2.48496109e-02] tensor(6830.9341)\n",
      "[1.00000000e+00 8.42000000e+02 0.00000000e+00 1.00000000e+00\n",
      " 2.30000000e+01 1.13000000e+02 0.00000000e+00 2.00000000e+00\n",
      " 3.00000000e+00 3.00000000e+00 0.00000000e+00 0.00000000e+00\n",
      " 0.00000000e+00 3.00000000e+01 2.00470543e-01] tensor(7288.6064)\n",
      "[2.00000000e+00 1.24500000e+03 0.00000000e+00 1.00000000e+00\n",
      " 4.20000000e+01 8.60000000e+01 0.00000000e+00 0.00000000e+00\n",
      " 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00\n",
      " 0.00000000e+00 2.90000000e+01 1.18880493e+00] tensor(10000.)\n",
      "[1.0000000e+00 8.4100000e+02 0.0000000e+00 1.0000000e+00 3.4000000e+01\n",
      " 1.1200000e+02 0.0000000e+00 2.0000000e+00 0.0000000e+00 0.0000000e+00\n",
      " 0.0000000e+00 0.0000000e+00 0.0000000e+00 3.3000000e+01 5.1998844e-01] tensor(8000.)\n",
      "[  1.         160.           1.           1.          36.\n",
      " 109.           0.           2.           0.           0.\n",
      "   0.           0.           0.          33.          -1.18132525] tensor(4553.9561)\n",
      "[  2.         851.           0.           1.          42.\n",
      "  86.           0.           0.           0.           0.\n",
      "   0.           0.           0.          33.          -1.04358761] tensor(4859.0713)\n",
      "[  2.         285.           0.           1.          25.\n",
      " 102.           0.           2.           0.           0.\n",
      "   0.           0.           0.          13.          -1.29818526] tensor(4268.)\n",
      "[  1.         554.           1.           1.          34.\n",
      " 113.           0.           2.           0.           0.\n",
      "   0.           0.           0.          18.          -0.88503262] tensor(5184.6289)\n",
      "[1.00000000e+00 7.34000000e+02 1.00000000e+00 1.00000000e+00\n",
      " 3.40000000e+01 1.08000000e+02 0.00000000e+00 2.00000000e+00\n",
      " 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00\n",
      " 0.00000000e+00 3.30000000e+01 1.43569229e-01] tensor(7170.3403)\n",
      "[  1.          45.           0.           1.          30.\n",
      " 106.           0.           2.           0.           0.\n",
      "   0.           0.           0.          31.           1.34300582] tensor(10670.)\n",
      "[  1.         336.           0.           1.          30.\n",
      " 104.           0.           2.           3.           0.\n",
      "   0.           0.           0.          31.          -1.29818526] tensor(4268.)\n",
      "[  2.         944.           0.           1.          29.\n",
      " 111.           1.           0.           0.           0.\n",
      "   0.           0.           0.          33.           1.82760652] tensor(15000.)\n",
      "[2.00000000e+00 1.70300000e+03 0.00000000e+00 0.00000000e+00\n",
      " 3.90000000e+01 1.17000000e+02 1.00000000e+00 0.00000000e+00\n",
      " 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00\n",
      " 0.00000000e+00 3.00000000e+01 1.82760652e+00] tensor(15000.)\n",
      "[  1.         757.           0.           1.          30.\n",
      " 103.           0.           2.           0.           0.\n",
      "   0.           0.           0.          27.          -1.29818526] tensor(4268.)\n",
      "[  2.         160.           1.           1.          38.\n",
      " 114.           1.           0.           0.           0.\n",
      "   0.           0.           0.          33.          -1.39501774] tensor(4000.)\n",
      "[  2.         285.           0.           1.          23.\n",
      " 113.           0.           2.           0.           0.\n",
      "   0.           0.           0.          30.           1.42012124] tensor(11063.9980)\n",
      "[  2.          10.           0.           1.          25.\n",
      " 103.           0.           2.           0.           0.\n",
      "   0.           0.           0.          13.           1.47629237] tensor(11384.8896)\n",
      "[  1.         652.           0.           1.          42.\n",
      "  86.           0.           0.           0.           0.\n",
      "   0.           0.           0.          29.           0.73256683] tensor(8536.)\n",
      "[1.00000000e+00 6.52000000e+02 0.00000000e+00 1.00000000e+00\n",
      " 3.00000000e+01 1.08000000e+02 0.00000000e+00 2.00000000e+00\n",
      " 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00\n",
      " 0.00000000e+00 3.30000000e+01 3.68223674e-01] tensor(7650.7529)\n",
      "[  1.         543.           0.           1.          34.\n",
      " 108.           0.           2.           3.           3.\n",
      "   0.           0.           0.          33.          -1.04358761] tensor(4859.0713)\n",
      "[  1.         554.           1.           1.          30.\n",
      " 106.           0.           2.           0.           0.\n",
      "   0.           0.           0.          33.          -1.39501774] tensor(4000.)\n",
      "[  2.         734.           1.           1.          32.\n",
      " 117.           1.           0.           0.           0.\n",
      "   0.           0.           0.          31.           1.34300582] tensor(10670.)\n",
      "[ 1.00000000e+00  7.30000000e+02  0.00000000e+00  1.00000000e+00\n",
      "  3.00000000e+01  1.17000000e+02  0.00000000e+00  2.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  3.30000000e+01 -4.59278471e-01] tensor(6000.)\n",
      "[1.2000000e+01 1.7030000e+03 0.0000000e+00 0.0000000e+00 3.1000000e+01\n",
      " 1.2100000e+02 0.0000000e+00 2.0000000e+00 3.0000000e+00 3.0000000e+00\n",
      " 4.0000000e+00 0.0000000e+00 3.0000000e+00 3.1000000e+01 5.1998844e-01] tensor(8000.)\n",
      "[  1.           9.           0.           1.          26.\n",
      " 117.           0.           2.           0.           0.\n",
      "   0.           0.           0.          31.          -0.88503262] tensor(5184.6289)\n",
      "[2.00000000e+00 8.52000000e+02 0.00000000e+00 1.00000000e+00\n",
      " 2.90000000e+01 1.06000000e+02 1.00000000e+00 0.00000000e+00\n",
      " 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00\n",
      " 0.00000000e+00 3.30000000e+01 7.32566829e-01] tensor(8536.)\n",
      "[  1.           9.           0.           1.          50.\n",
      " 127.           0.           2.           0.           0.\n",
      "   0.           0.           0.          33.          -0.30114386] tensor(6298.1201)\n",
      "[  1.         160.           1.           1.          26.\n",
      " 106.           0.           2.           0.           0.\n",
      "   0.           0.           0.          33.          -0.51104337] tensor(5902.6431)\n",
      "[  2.         160.           1.           1.          23.\n",
      " 113.           1.           0.           0.           0.\n",
      "   0.           0.           0.          30.          -1.29818526] tensor(4268.)\n",
      "[  6.         407.           1.           1.          42.\n",
      "  86.           0.           0.           0.           0.\n",
      "   0.           0.           0.          28.          -0.70677457] tensor(5531.9990)\n",
      "[  1.         552.           0.           1.          34.\n",
      " 108.           0.           2.           0.           0.\n",
      "   0.           0.           0.          33.          -1.39501774] tensor(4000.)\n",
      "[2.0000000e+00 7.4700000e+02 0.0000000e+00 1.0000000e+00 4.2000000e+01\n",
      " 8.6000000e+01 0.0000000e+00 0.0000000e+00 0.0000000e+00 0.0000000e+00\n",
      " 0.0000000e+00 0.0000000e+00 0.0000000e+00 3.0000000e+01 5.1998844e-01] tensor(8000.)\n",
      "[ 2.00000000e+00  4.65000000e+02  0.00000000e+00  1.00000000e+00\n",
      "  4.20000000e+01  8.60000000e+01  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  3.00000000e+01 -8.13051736e-02] tensor(6720.0938)\n",
      "[1.00000000e+00 8.41000000e+02 0.00000000e+00 1.00000000e+00\n",
      " 3.00000000e+01 1.14000000e+02 0.00000000e+00 2.00000000e+00\n",
      " 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00\n",
      " 0.00000000e+00 3.00000000e+01 2.00470543e-01] tensor(7288.6064)\n",
      "[  1.         847.           0.           1.          42.\n",
      "  86.           0.           0.           0.           0.\n",
      "   0.           0.           0.          33.           1.58881165] tensor(12147.6777)\n",
      "[  2.           9.           0.           1.          34.\n",
      " 113.           0.           2.           0.           0.\n",
      "   0.           0.           0.          33.          -1.39501774] tensor(4000.)\n",
      "[  1.         289.           0.           1.          32.\n",
      " 118.           0.           2.           3.           3.\n",
      "   0.           0.           0.          33.          -0.30114386] tensor(6298.1201)\n",
      "[  2.         200.           0.           1.          28.\n",
      " 115.           0.           2.           0.           0.\n",
      "   0.           0.           0.          33.          -1.29818526] tensor(4268.)\n",
      "[ 6.00000000e+00  7.53000000e+02  0.00000000e+00  1.00000000e+00\n",
      "  3.20000000e+01  1.17000000e+02  1.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  3.30000000e+01 -2.46441106e-01] tensor(6402.)\n",
      "[ 1.00000000e+00  8.11000000e+02  0.00000000e+00  0.00000000e+00\n",
      "  3.80000000e+01  1.15000000e+02  0.00000000e+00  2.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  3.30000000e+01 -2.46441106e-01] tensor(6402.)\n",
      "[ 2.00000000e+00  1.59000000e+02  1.00000000e+00  1.00000000e+00\n",
      "  2.20000000e+01  1.14000000e+02  1.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  3.10000000e+01 -2.48496109e-02] tensor(6830.9341)\n",
      "[  1.         649.           0.           1.          36.\n",
      " 103.           0.           2.           0.           0.\n",
      "   0.           0.           0.          33.          -1.18132525] tensor(4553.9561)\n",
      "[  1.         869.           0.           1.          31.\n",
      " 104.           0.           2.           0.           0.\n",
      "   0.           0.           0.          27.          -1.18132525] tensor(4553.9561)\n",
      "[  1.         160.           1.           1.          28.\n",
      " 115.           0.           2.           0.           0.\n",
      "   0.           0.           0.          33.          -1.18132525] tensor(4553.9561)\n",
      "[  1.        160.          1.          1.         39.        116.\n",
      "   0.          2.          3.          3.          0.          0.\n",
      "   0.         26.          1.2775747] tensor(10369.2578)\n",
      "[  1.           9.           0.           1.          43.\n",
      " 126.           0.           2.           0.           0.\n",
      "   0.           0.           0.          31.          -1.04358761] tensor(4859.0713)\n",
      "[ 2.00000000e+00  1.51500000e+03  0.00000000e+00  1.00000000e+00\n",
      "  2.30000000e+01  1.13000000e+02  1.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  3.30000000e+01 -2.48496109e-02] tensor(6830.9341)\n",
      "[  1.         747.           0.           1.          32.\n",
      " 112.           0.           2.           0.           0.\n",
      "   0.           0.           0.          18.          -1.39501774] tensor(4000.)\n",
      "[ 12.         160.           1.           1.          39.\n",
      " 116.           0.           2.           3.           3.\n",
      "   0.           0.           3.          31.           1.96949696] tensor(26888.7754)\n",
      "[ 2.00000000e+00  8.40000000e+02  0.00000000e+00  1.00000000e+00\n",
      "  4.90000000e+01  1.19000000e+02  0.00000000e+00  2.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  9.00000000e+00 -7.06774568e-01] tensor(5531.9990)\n",
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      "[ 2.         54.          0.          1.         39.          0.\n",
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      "[  1.           9.           0.           1.          32.\n",
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      "[  1.         649.           0.           1.          43.\n",
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      "[  2.         851.           0.           1.          36.\n",
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      "[  1.         842.           0.           1.          23.\n",
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      "[  1.         230.           0.           1.          41.\n",
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      "[ 12.         592.           0.           1.          31.\n",
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      "[  1.         652.           0.           1.          31.\n",
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      "[  1.         848.           0.           1.          40.\n",
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      "[  1.         652.           0.           1.          42.\n",
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      "[ 12.         159.           1.           1.          22.\n",
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      "[  2.         159.           1.           1.          42.\n",
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      "[  2.         655.           0.           1.          37.\n",
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      "[  1.         159.           1.           1.          32.\n",
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      "[  2.         840.           0.           1.          32.\n",
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      "[  2.         747.           0.           1.          34.\n",
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      "   0.           0.           0.          20.          -1.39501774] tensor(4000.)\n",
      "[ 2.00000000e+00  1.70300000e+03  0.00000000e+00  0.00000000e+00\n",
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     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "  0.00000000e+00  3.30000000e+01 -2.48496109e-02] tensor(6830.9341)\n",
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      " 114.           0.           2.           0.           0.\n",
      "   0.           0.           0.          33.           1.18880493] tensor(10000.)\n",
      "[ 1.00000000e+00  9.44000000e+02  0.00000000e+00  1.00000000e+00\n",
      "  2.20000000e+01  1.13000000e+02  0.00000000e+00  2.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  3.10000000e+01 -8.85032618e-01] tensor(5184.6289)\n",
      "[ 1.00000000e+00  7.47000000e+02  0.00000000e+00  1.00000000e+00\n",
      "  3.70000000e+01  1.12000000e+02  0.00000000e+00  2.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  3.10000000e+01 -4.59278471e-01] tensor(6000.)\n",
      "[ 2.00000000e+00  1.51800000e+03  0.00000000e+00  1.00000000e+00\n",
      "  3.70000000e+01  1.14000000e+02  1.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  3.10000000e+01 -1.04358761e+00] tensor(4859.0713)\n",
      "[  2.         160.           1.           1.          29.\n",
      " 116.           0.           2.           0.           0.\n",
      "   0.           0.           0.          33.          -1.29818526] tensor(4268.)\n",
      "[ 2.00000000e+00  1.70300000e+03  0.00000000e+00  0.00000000e+00\n",
      "  3.50000000e+01  1.16000000e+02  1.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  3.30000000e+01 -1.18132525e+00] tensor(4553.9561)\n",
      "[ 1.00000000e+00  7.36000000e+02  0.00000000e+00  1.00000000e+00\n",
      "  2.80000000e+01  1.12000000e+02  0.00000000e+00  2.00000000e+00\n",
      "  3.00000000e+00  3.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  3.00000000e+00  3.10000000e+01 -5.11043371e-01] tensor(5902.6431)\n",
      "[ 12.         159.           1.           1.          30.\n",
      " 103.           0.           2.           3.           3.\n",
      "   0.           0.           0.          33.           1.86966682] tensor(16005.)\n",
      "[  1.           9.           0.           1.          31.\n",
      " 120.           0.           2.           0.           0.\n",
      "   0.           0.           0.          33.           0.20047054] tensor(7288.6064)\n",
      "[ 9.00000000e+00  1.70300000e+03  0.00000000e+00  0.00000000e+00\n",
      "  3.60000000e+01  1.14000000e+02  1.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  3.30000000e+01 -4.59278471e-01] tensor(6000.)\n",
      "[ 2.00000000e+00  1.70300000e+03  0.00000000e+00  0.00000000e+00\n",
      "  2.90000000e+01  1.06000000e+02  0.00000000e+00  2.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  3.30000000e+01 -1.29818526e+00] tensor(4268.)\n",
      "[  1.         160.           1.           1.          29.\n",
      " 119.           0.           2.           0.           0.\n",
      "   0.           0.           0.          28.           1.11436842] tensor(9718.1426)\n",
      "[ 2.00000000e+00  8.42000000e+02  0.00000000e+00  1.00000000e+00\n",
      "  2.30000000e+01  1.13000000e+02  0.00000000e+00  2.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  3.00000000e+01 -2.48496109e-02] tensor(6830.9341)\n",
      "[  1.         635.           0.           1.          39.\n",
      " 117.           0.           2.           0.           0.\n",
      "   0.           0.           0.          31.          -0.70677457] tensor(5531.9990)\n",
      "[ 1.00000000e+00  7.34000000e+02  1.00000000e+00  1.00000000e+00\n",
      "  3.20000000e+01  1.18000000e+02  0.00000000e+00  2.00000000e+00\n",
      "  3.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  2.60000000e+01 -3.01143857e-01] tensor(6298.1201)\n",
      "[  1.         739.           0.           1.          38.\n",
      " 115.           0.           2.           0.           0.\n",
      "   0.           0.           0.          19.          -0.88503262] tensor(5184.6289)\n",
      "[1.00000000e+00 7.47000000e+02 0.00000000e+00 1.00000000e+00\n",
      " 3.00000000e+01 1.03000000e+02 0.00000000e+00 2.00000000e+00\n",
      " 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00\n",
      " 0.00000000e+00 3.10000000e+01 2.00470543e-01] tensor(7288.6064)\n",
      "[  2.          65.           0.           0.          38.\n",
      " 114.           0.           2.           0.           0.\n",
      "   0.           0.           0.          31.           1.79095162] tensor(14340.6807)\n",
      "[  2.         635.           0.           1.          34.\n",
      " 115.           0.           2.           0.           0.\n",
      "   0.           0.           0.          31.          -1.29818526] tensor(4268.)\n",
      "[  1.         652.           0.           1.          44.\n",
      " 129.           0.           2.           0.           0.\n",
      "   0.           0.           0.          33.          -0.88503262] tensor(5184.6289)\n",
      "[  1.         200.           0.           1.          41.\n",
      " 113.           0.           2.           0.           0.\n",
      "   0.           0.           0.          33.          -1.04358761] tensor(4859.0713)\n",
      "[2.00000000e+00 7.12000000e+02 0.00000000e+00 1.00000000e+00\n",
      " 2.70000000e+01 1.11000000e+02 0.00000000e+00 2.00000000e+00\n",
      " 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00\n",
      " 0.00000000e+00 3.10000000e+01 1.43569229e-01] tensor(7170.3403)\n",
      "[ 2.00000000e+00  1.42900000e+03  0.00000000e+00  1.00000000e+00\n",
      "  2.80000000e+01  1.13000000e+02  1.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  3.00000000e+01 -1.39501774e+00] tensor(4000.)\n",
      "[  1.         840.           0.           1.          42.\n",
      "  86.           0.           0.           0.           0.\n",
      "   0.           0.           0.          33.           1.75628398] tensor(13829.9971)\n",
      "[1.00000000e+00 1.70300000e+03 0.00000000e+00 0.00000000e+00\n",
      " 2.20000000e+01 1.13000000e+02 0.00000000e+00 2.00000000e+00\n",
      " 3.00000000e+00 3.00000000e+00 0.00000000e+00 0.00000000e+00\n",
      " 3.00000000e+00 3.30000000e+01 1.68158211e+00] tensor(12961.5723)\n",
      "[1.0000000e+00 1.7030000e+03 0.0000000e+00 0.0000000e+00 4.3000000e+01\n",
      " 1.2500000e+02 0.0000000e+00 2.0000000e+00 0.0000000e+00 0.0000000e+00\n",
      " 0.0000000e+00 0.0000000e+00 0.0000000e+00 3.1000000e+01 1.2775747e+00] tensor(10369.2578)\n",
      "[ 1.00000000e+00  8.56000000e+02  0.00000000e+00  1.00000000e+00\n",
      "  3.20000000e+01  1.18000000e+02  0.00000000e+00  2.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  2.60000000e+01 -3.01143857e-01] tensor(6298.1201)\n",
      "[  1.         836.           0.           1.          34.\n",
      " 108.           0.           2.           3.           3.\n",
      "   0.           0.           0.          33.           1.11436842] tensor(9718.1426)\n",
      "[  1.         840.           0.           1.          30.\n",
      " 114.           0.           2.           0.           0.\n",
      "   0.           0.           0.          33.          -1.18132525] tensor(4553.9561)\n",
      "[  1.         754.           0.           1.          42.\n",
      "  86.           0.           0.           0.           0.\n",
      "   0.           0.           0.          33.          -1.04358761] tensor(4859.0713)\n",
      "[  1.         652.           0.           1.          31.\n",
      " 121.           0.           2.           0.           0.\n",
      "   0.           0.           0.          33.           1.36054634] tensor(10755.5107)\n",
      "[ 2.00000000e+00  7.48000000e+02  0.00000000e+00  1.00000000e+00\n",
      "  3.70000000e+01  1.14000000e+02  1.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  3.30000000e+01 -5.11043371e-01] tensor(5902.6431)\n",
      "[  1.         159.           1.           1.          39.\n",
      " 116.           0.           2.           3.           3.\n",
      "   0.           0.           3.          31.           0.20047054] tensor(7288.6064)\n",
      "[  2.         629.           0.           1.          28.\n",
      " 115.           1.           0.           0.           0.\n",
      "   0.           0.           0.          14.          -0.70677457] tensor(5531.9990)\n",
      "[  2.         635.           0.           1.          22.\n",
      " 108.           0.           2.           0.           0.\n",
      "   0.           0.           0.          33.           0.79629725] tensor(8710.2979)\n",
      "[  1.         159.           1.           1.          39.\n",
      " 116.           0.           2.           3.           3.\n",
      "   0.           0.           0.          31.           0.84684595] tensor(8853.9639)\n",
      "[  2.         743.           0.           1.          30.\n",
      " 115.           0.           2.           0.           0.\n",
      "   0.           0.           0.          14.           1.11436842] tensor(9718.1426)\n",
      "[  1.         749.           0.           1.          31.\n",
      " 120.           0.           2.           0.           0.\n",
      "   0.           0.           0.          33.           1.11436842] tensor(9718.1426)\n",
      "[ 2.00000000e+00  6.49000000e+02  0.00000000e+00  1.00000000e+00\n",
      "  3.40000000e+01  1.14000000e+02  0.00000000e+00  2.00000000e+00\n",
      "  3.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  3.30000000e+01 -4.59278471e-01] tensor(6000.)\n",
      "[ 2.00000000e+00  1.70300000e+03  0.00000000e+00  0.00000000e+00\n",
      "  4.20000000e+01  8.60000000e+01  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  2.90000000e+01 -8.13051736e-02] tensor(6720.0938)\n",
      "[1.00000000e+00 7.48000000e+02 0.00000000e+00 1.00000000e+00\n",
      " 3.10000000e+01 1.19000000e+02 0.00000000e+00 2.00000000e+00\n",
      " 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00\n",
      " 0.00000000e+00 3.30000000e+01 4.24233531e-01] tensor(7776.9434)\n",
      "[  2.          54.           0.           1.          34.\n",
      " 113.           0.           2.           0.           0.\n",
      "   0.           0.           0.          33.          -0.88503262] tensor(5184.6289)\n",
      "[  2.         407.           1.           1.          39.\n",
      " 117.           0.           2.           0.           0.\n",
      "   0.           0.           0.          22.          -1.29818526] tensor(4268.)\n",
      "[ 2.00000000e+00  7.34000000e+02  1.00000000e+00  1.00000000e+00\n",
      "  3.40000000e+01  1.09000000e+02  1.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  3.30000000e+01 -8.13051736e-02] tensor(6720.0938)\n",
      "[1.00000000e+00 1.70300000e+03 0.00000000e+00 0.00000000e+00\n",
      " 3.70000000e+01 1.13000000e+02 0.00000000e+00 2.00000000e+00\n",
      " 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00\n",
      " 0.00000000e+00 3.10000000e+01 1.58881165e+00] tensor(12147.6777)\n",
      "[  2.         159.           1.           1.          37.\n",
      " 121.           0.           2.           0.           0.\n",
      "   0.           0.           0.          33.          -0.70677457] tensor(5531.9990)\n",
      "[ 1.00000000e+00  1.70300000e+03  0.00000000e+00  0.00000000e+00\n",
      "  3.40000000e+01  1.13000000e+02  0.00000000e+00  2.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  8.00000000e+00 -1.39501774e+00] tensor(4000.)\n",
      "[2.00000000e+00 1.70300000e+03 0.00000000e+00 0.00000000e+00\n",
      " 4.20000000e+01 8.60000000e+01 0.00000000e+00 0.00000000e+00\n",
      " 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00\n",
      " 0.00000000e+00 3.30000000e+01 2.00470543e-01] tensor(7288.6064)\n",
      "[1.00000000e+00 6.52000000e+02 0.00000000e+00 1.00000000e+00\n",
      " 3.20000000e+01 1.18000000e+02 0.00000000e+00 2.00000000e+00\n",
      " 3.00000000e+00 3.00000000e+00 0.00000000e+00 0.00000000e+00\n",
      " 0.00000000e+00 2.60000000e+01 6.41262404e-01] tensor(8297.9980)\n",
      "[  1.         407.           1.           1.          39.\n",
      " 117.           0.           2.           3.           3.\n",
      "   0.           0.           3.          31.          -0.70677457] tensor(5531.9990)\n",
      "[  2.         851.           0.           1.          27.\n",
      " 118.           0.           2.           0.           0.\n",
      "   0.           0.           0.          21.          -1.18132525] tensor(4553.9561)\n",
      "[  2.         197.           0.           1.          42.\n",
      "  86.           0.           0.           0.           0.\n",
      "   0.           0.           0.          14.          -1.18132525] tensor(4553.9561)\n",
      "[ 3.00000000e+00  9.44000000e+02  0.00000000e+00  1.00000000e+00\n",
      "  4.20000000e+01  8.60000000e+01  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  3.00000000e+01 -7.06774568e-01] tensor(5531.9990)\n",
      "[4.00000000e+00 4.71000000e+02 0.00000000e+00 1.00000000e+00\n",
      " 4.20000000e+01 8.60000000e+01 0.00000000e+00 0.00000000e+00\n",
      " 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00\n",
      " 0.00000000e+00 2.90000000e+01 4.24233531e-01] tensor(7776.9434)\n",
      "[2.00000000e+00 1.01800000e+03 0.00000000e+00 1.00000000e+00\n",
      " 4.20000000e+01 8.60000000e+01 0.00000000e+00 0.00000000e+00\n",
      " 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00\n",
      " 0.00000000e+00 3.30000000e+01 3.68223674e-01] tensor(7650.7529)\n",
      "[ 2.00000000e+00  8.51000000e+02  0.00000000e+00  1.00000000e+00\n",
      "  2.40000000e+01  1.18000000e+02  1.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  3.00000000e+01 -2.48496109e-02] tensor(6830.9341)\n",
      "[  2.         734.           1.           1.          33.\n",
      " 107.           1.           0.           0.           0.\n",
      "   0.           0.           0.          33.           0.84684595] tensor(8853.9639)\n",
      "[  1.         311.           0.           1.          23.\n",
      " 113.           0.           2.           0.           0.\n",
      "   0.           0.           0.          30.           0.93187116] tensor(9107.9121)\n",
      "[  1.         629.           0.           1.          30.\n",
      " 103.           0.           2.           0.           0.\n",
      "   0.           0.           0.          33.          -1.04358761] tensor(4859.0713)\n",
      "[ 1.00000000e+00  8.42000000e+02  0.00000000e+00  1.00000000e+00\n",
      "  3.60000000e+01  1.20000000e+02  0.00000000e+00  2.00000000e+00\n",
      "  3.00000000e+00  3.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  3.00000000e+00  3.30000000e+01 -4.59278471e-01] tensor(6000.)\n",
      "[  2.         870.           0.           1.          31.\n",
      " 119.           1.           0.           0.           0.\n",
      "   0.           0.           0.          31.          -1.04358761] tensor(4859.0713)\n",
      "[  2.         852.           0.           1.          36.\n",
      " 117.           1.           0.           0.           0.\n",
      "   0.           0.           0.          33.          -1.29818526] tensor(4268.)\n",
      "[ 2.00000000e+00  1.70300000e+03  0.00000000e+00  0.00000000e+00\n",
      "  3.60000000e+01  1.18000000e+02  0.00000000e+00  2.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  2.30000000e+01 -8.13051736e-02] tensor(6720.0938)\n",
      "[  2.         269.           0.           1.          40.\n",
      " 120.           1.           0.           0.           0.\n",
      "   0.           0.           0.          26.           1.58881165] tensor(12147.6777)\n",
      "[ 1.00000000e+00  7.36000000e+02  0.00000000e+00  1.00000000e+00\n",
      "  3.40000000e+01  1.13000000e+02  0.00000000e+00  2.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  3.30000000e+01 -4.59278471e-01] tensor(6000.)\n",
      "[  1.           9.           0.           1.          39.\n",
      " 116.           0.           2.           0.           0.\n",
      "   0.           0.           0.          19.          -1.04358761] tensor(4859.0713)\n",
      "[ 1.00000000e+00  1.70300000e+03  0.00000000e+00  0.00000000e+00\n",
      "  2.50000000e+01  1.02000000e+02  0.00000000e+00  2.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  3.30000000e+01 -1.18132525e+00] tensor(4553.9561)\n",
      "[  1.         407.           1.           1.          27.\n",
      " 120.           0.           2.           0.           0.\n",
      "   0.           0.           0.          31.           1.54171779] tensor(11805.2861)\n",
      "[  1.         289.           0.           1.          30.\n",
      " 114.           0.           2.           3.           3.\n",
      "   0.           0.           0.          31.           0.93187116] tensor(9107.9121)\n",
      "[  2.         543.           0.           1.          30.\n",
      " 111.           1.           0.           0.           0.\n",
      "   0.           0.           0.          33.           0.93187116] tensor(9107.9121)\n",
      "[ 1.00000000e+00  7.34000000e+02  1.00000000e+00  1.00000000e+00\n",
      "  4.00000000e+01  1.16000000e+02  0.00000000e+00  2.00000000e+00\n",
      "  3.00000000e+00  3.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  3.30000000e+01 -5.11043371e-01] tensor(5902.6431)\n",
      "[ 2.         22.          0.          0.         42.         86.\n",
      "  0.          0.          0.          0.          0.          0.\n",
      "  0.         31.         -0.24644111] tensor(6402.)\n",
      "[ 2.00000000e+00  1.70300000e+03  0.00000000e+00  0.00000000e+00\n",
      "  3.90000000e+01  1.19000000e+02  1.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  3.10000000e+01 -1.29818526e+00] tensor(4268.)\n",
      "[  1.         159.           1.           1.          45.\n",
      " 126.           0.           2.           0.           0.\n",
      "   0.           0.           0.          33.          -0.88503262] tensor(5184.6289)\n",
      "[  1.         471.           0.           1.          43.\n",
      " 126.           0.           2.           0.           0.\n",
      "   0.           0.           0.          33.          -1.18132525] tensor(4553.9561)\n",
      "[  2.         660.           0.           1.          37.\n",
      " 114.           0.           2.           0.           0.\n",
      "   0.           0.           0.          33.          -1.04358761] tensor(4859.0713)\n",
      "[  1.         159.           1.           1.          42.\n",
      "  86.           0.           0.           0.           0.\n",
      "   0.           0.           0.          31.           0.20047054] tensor(7288.6064)\n",
      "[  1.         348.           0.           1.          31.\n",
      " 121.           0.           2.           0.           0.\n",
      "   0.           0.           0.          33.           1.82760652] tensor(15000.)\n",
      "[ 2.00000000e+00  1.44800000e+03  0.00000000e+00  1.00000000e+00\n",
      "  3.10000000e+01  1.20000000e+02  1.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  3.30000000e+01 -4.59278471e-01] tensor(6000.)\n",
      "[  1.         734.           1.           1.          45.\n",
      " 126.           0.           2.           3.           3.\n",
      "   4.           0.           3.          33.           1.58881165] tensor(12147.6777)\n",
      "[  1.         851.           0.           1.          42.\n",
      "  86.           0.           0.           0.           0.\n",
      "   0.           0.           0.          31.          -1.04358761] tensor(4859.0713)\n",
      "[  2.         200.           0.           1.          34.\n",
      " 107.           1.           0.           0.           0.\n",
      "   0.           0.           0.          31.          -1.29818526] tensor(4268.)\n",
      "[ 3.         67.          0.          1.         42.         86.\n",
      "  0.          0.          0.          0.          0.          0.\n",
      "  0.         16.         -0.70677457] tensor(5531.9990)\n",
      "[  2.         160.           1.           1.          40.\n",
      " 114.           0.           2.           0.           0.\n",
      "   0.           0.           0.          31.          -0.45927847] tensor(6000.)\n",
      "[  2.         840.           0.           1.          42.\n",
      "  86.           0.           0.           0.           0.\n",
      "   0.           0.           0.          33.          -0.88503262] tensor(5184.6289)\n",
      "[2.00000000e+00 1.70300000e+03 0.00000000e+00 0.00000000e+00\n",
      " 4.20000000e+01 8.60000000e+01 0.00000000e+00 0.00000000e+00\n",
      " 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00\n",
      " 0.00000000e+00 3.10000000e+01 9.31871161e-01] tensor(9107.9121)\n",
      "[ 1.20000000e+01  7.18000000e+02  0.00000000e+00  1.00000000e+00\n",
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      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  1.60000000e+01 -2.46441106e-01] tensor(6402.)\n",
      "[  1.         749.           0.           1.          30.\n",
      " 120.           0.           2.           0.           0.\n",
      "   0.           0.           0.          28.           1.96929153] tensor(26675.)\n",
      "[ 1.00000000e+00  6.35000000e+02  0.00000000e+00  1.00000000e+00\n",
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      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  3.30000000e+01 -2.46441106e-01] tensor(6402.)\n",
      "[ 1.00000000e+00  8.41000000e+02  0.00000000e+00  1.00000000e+00\n",
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      "  0.00000000e+00  3.10000000e+01 -4.59278471e-01] tensor(6000.)\n",
      "[ 2.00000000e+00  6.58000000e+02  0.00000000e+00  1.00000000e+00\n",
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      "  0.00000000e+00  2.20000000e+01 -2.48496109e-02] tensor(6830.9341)\n",
      "[ 2.00000000e+00  9.44000000e+02  0.00000000e+00  1.00000000e+00\n",
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      "  0.00000000e+00  2.70000000e+01 -5.11043371e-01] tensor(5902.6431)\n",
      "[ 1.00000000e+00  8.37000000e+02  0.00000000e+00  1.00000000e+00\n",
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      "  0.00000000e+00  3.30000000e+01 -7.06774568e-01] tensor(5531.9990)\n",
      "[ 1.00000000e+00  3.48000000e+02  0.00000000e+00  1.00000000e+00\n",
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      "  0.00000000e+00  3.00000000e+01 -2.48496109e-02] tensor(6830.9341)\n",
      "[  1.        629.          0.          1.         39.        116.\n",
      "   0.          2.          3.          3.          0.          0.\n",
      "   3.         31.          1.9010312] tensor(17077.3359)\n",
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      " 3.40000000e+01 1.09000000e+02 0.00000000e+00 2.00000000e+00\n",
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      " 0.00000000e+00 2.70000000e+01 3.68223674e-01] tensor(7650.7529)\n",
      "[  2.         652.           0.           1.          37.\n",
      " 114.           0.           2.           0.           0.\n",
      "   0.           0.           0.           9.          -1.29818526] tensor(4268.)\n",
      "[  1.         814.           0.           1.          43.\n",
      " 126.           0.           2.           0.           0.\n",
      "   0.           0.           0.           9.          -0.88503262] tensor(5184.6289)\n",
      "[ 2.00000000e+00  1.70300000e+03  0.00000000e+00  0.00000000e+00\n",
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      "  0.00000000e+00  3.30000000e+01 -2.48496109e-02] tensor(6830.9341)\n",
      "[ 2.00000000e+00  8.61000000e+02  0.00000000e+00  0.00000000e+00\n",
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      "  0.00000000e+00  3.30000000e+01 -2.48496109e-02] tensor(6830.9341)\n",
      "[  1.          10.           0.           1.          35.\n",
      " 113.           0.           2.           0.           0.\n",
      "   0.           0.           0.          33.          -0.30114386] tensor(6298.1201)\n",
      "[  1.          10.           0.           1.          34.\n",
      " 113.           0.           2.           0.           0.\n",
      "   0.           0.           0.          33.          -1.04358761] tensor(4859.0713)\n",
      "[ 2.00000000e+00  1.70300000e+03  0.00000000e+00  0.00000000e+00\n",
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      "  0.00000000e+00  2.80000000e+01 -5.11043371e-01] tensor(5902.6431)\n",
      "[  1.         554.           1.           1.          42.\n",
      "  86.           0.           0.           0.           0.\n",
      "   0.           0.           0.          33.          -0.88503262] tensor(5184.6289)\n",
      "[  2.         842.           0.           1.          35.\n",
      " 113.           1.           0.           0.           0.\n",
      "   0.           0.           0.          33.          -0.88503262] tensor(5184.6289)\n",
      "[2.00000000e+00 9.44000000e+02 0.00000000e+00 1.00000000e+00\n",
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      " 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00\n",
      " 0.00000000e+00 2.70000000e+01 4.24233531e-01] tensor(7776.9434)\n",
      "[  2.         167.           0.           1.          22.\n",
      " 113.           0.           2.           0.           0.\n",
      "   0.           0.           0.          30.           1.34300582] tensor(10670.)\n",
      "[  1.         719.           0.           1.          35.\n",
      " 103.           0.           2.           0.           0.\n",
      "   0.           0.           0.          10.           1.18880493] tensor(10000.)\n",
      "[ 2.00000000e+00  1.70300000e+03  0.00000000e+00  0.00000000e+00\n",
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      "  0.00000000e+00  2.90000000e+01 -8.85032618e-01] tensor(5184.6289)\n",
      "[ 8.00000000e+00  9.44000000e+02  0.00000000e+00  1.00000000e+00\n",
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      "  0.00000000e+00  3.00000000e+01 -2.48496109e-02] tensor(6830.9341)\n",
      "[2.00000000e+00 6.49000000e+02 0.00000000e+00 1.00000000e+00\n",
      " 4.20000000e+01 8.60000000e+01 0.00000000e+00 0.00000000e+00\n",
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      " 0.00000000e+00 3.30000000e+01 4.24233531e-01] tensor(7776.9434)\n",
      "[ 1.00000000e+00  8.40000000e+02  0.00000000e+00  1.00000000e+00\n",
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      "  0.00000000e+00  3.10000000e+01 -8.13051736e-02] tensor(6720.0938)\n",
      "[  2.         160.           1.           1.          30.\n",
      " 117.           1.           0.           0.           0.\n",
      "   0.           0.           0.          33.          -1.29818526] tensor(4268.)\n",
      "[  1.         719.           0.           1.          28.\n",
      " 115.           0.           2.           0.           0.\n",
      "   0.           0.           0.          29.          -0.88503262] tensor(5184.6289)\n",
      "[ 2.00000000e+00  1.70300000e+03  0.00000000e+00  0.00000000e+00\n",
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      "  0.00000000e+00  2.00000000e+01 -8.85032618e-01] tensor(5184.6289)\n",
      "[ 2.00000000e+00  1.60000000e+02  1.00000000e+00  1.00000000e+00\n",
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      "  0.00000000e+00  3.00000000e+01 -2.48496109e-02] tensor(6830.9341)\n",
      "[  1.         407.           1.           1.          30.\n",
      " 103.           0.           2.           0.           0.\n",
      "   0.           0.           0.          27.           1.86015571] tensor(15745.2998)\n",
      "[  1.         554.           1.           1.          29.\n",
      " 106.           0.           2.           3.           3.\n",
      "   0.           0.           3.          33.           0.93187116] tensor(9107.9121)\n",
      "[1.00000000e+00 1.70300000e+03 0.00000000e+00 0.00000000e+00\n",
      " 4.20000000e+01 8.60000000e+01 0.00000000e+00 0.00000000e+00\n",
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      " 0.00000000e+00 2.90000000e+01 1.58881165e+00] tensor(12147.6777)\n",
      "[1.00000000e+00 1.70300000e+03 0.00000000e+00 0.00000000e+00\n",
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      " 3.00000000e+00 3.30000000e+01 1.58881165e+00] tensor(12147.6777)\n",
      "[ 2.00000000e+00  1.60900000e+03  0.00000000e+00  0.00000000e+00\n",
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      "  0.00000000e+00  3.10000000e+01 -1.04358761e+00] tensor(4859.0713)\n",
      "[  1.         847.           0.           1.          34.\n",
      " 108.           0.           2.           0.           0.\n",
      "   0.           0.           0.          33.          -1.18132525] tensor(4553.9561)\n",
      "[  3.          60.           0.           1.          31.\n",
      " 107.           1.           0.           0.           0.\n",
      "   0.           0.           0.          33.          -0.70677457] tensor(5531.9990)\n",
      "[2.00000000e+00 7.34000000e+02 1.00000000e+00 1.00000000e+00\n",
      " 4.30000000e+01 1.25000000e+02 1.00000000e+00 0.00000000e+00\n",
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      " 0.00000000e+00 3.30000000e+01 7.32566829e-01] tensor(8536.)\n",
      "[ 1.00000000e+00  7.69000000e+02  0.00000000e+00  0.00000000e+00\n",
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      "  0.00000000e+00  2.60000000e+01 -2.46441106e-01] tensor(6402.)\n",
      "[  1.         635.           0.           1.          23.\n",
      " 113.           0.           2.           0.           0.\n",
      "   0.           0.           0.          30.          -1.39501774] tensor(4000.)\n",
      "[  1.         734.           1.           1.          31.\n",
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      "[  1.         159.           1.           1.          30.\n",
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      "   0.           0.           0.          31.           1.11436842] tensor(9718.1426)\n",
      "[ 1.00000000e+00  1.70300000e+03  0.00000000e+00  0.00000000e+00\n",
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      "  0.00000000e+00  3.30000000e+01 -4.59278471e-01] tensor(6000.)\n",
      "[  1.         159.           1.           1.          25.\n",
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      "[  1.         160.           1.           1.          34.\n",
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      "[ 2.00000000e+00  9.00000000e+00  0.00000000e+00  1.00000000e+00\n",
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      "[ 2.00000000e+00  5.54000000e+02  1.00000000e+00  1.00000000e+00\n",
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      "  0.00000000e+00  3.30000000e+01 -3.01143857e-01] tensor(6298.1201)\n",
      "[  8.         840.           0.           1.          42.\n",
      "  86.           0.           0.           0.           0.\n",
      "   0.           0.           0.          33.           1.79095162] tensor(14340.6807)\n",
      "[ 2.00000000e+00  2.57000000e+02  1.00000000e+00  1.00000000e+00\n",
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      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  4.00000000e+00 -2.46441106e-01] tensor(6402.)\n",
      "[  1.        162.          0.          1.         22.        108.\n",
      "   0.          2.          0.          0.          0.          0.\n",
      "   0.         12.          1.2775747] tensor(10369.2578)\n",
      "[  1.         652.           0.           1.          42.\n",
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      "   0.           0.           0.          33.           1.20889385] tensor(10080.1406)\n",
      "[2.00000000e+00 7.52000000e+02 0.00000000e+00 1.00000000e+00\n",
      " 4.20000000e+01 8.60000000e+01 0.00000000e+00 0.00000000e+00\n",
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      " 0.00000000e+00 3.30000000e+01 4.24233531e-01] tensor(7776.9434)\n",
      "[  1.        407.          1.          1.         35.        104.\n",
      "   0.          2.          0.          0.          0.          0.\n",
      "   0.         29.          1.2775747] tensor(10369.2578)\n",
      "[  2.         652.           0.           1.          42.\n",
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      "   0.           0.           0.          33.           1.58881165] tensor(12147.6777)\n",
      "[  1.         764.           0.           1.          28.\n",
      " 115.           0.           2.           0.           0.\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "   0.           0.           0.          33.           1.86015571] tensor(15745.2998)\n",
      "[  2.         747.           0.           1.          42.\n",
      "  86.           0.           0.           0.           0.\n",
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      "[  1.         159.           1.           1.          31.\n",
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      " 3.40000000e+01 1.17000000e+02 0.00000000e+00 2.00000000e+00\n",
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      " 0.00000000e+00 2.60000000e+01 2.00470543e-01] tensor(7288.6064)\n",
      "[ 2.00000000e+00  1.70300000e+03  0.00000000e+00  0.00000000e+00\n",
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      "[ 1.00000000e+00  7.34000000e+02  1.00000000e+00  1.00000000e+00\n",
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      "[ 1.00000000e+00  1.70300000e+03  0.00000000e+00  0.00000000e+00\n",
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      "[  1.         840.           0.           1.          29.\n",
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      "[  1.         235.           0.           1.          29.\n",
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      "[ 2.00000000e+00  1.23500000e+03  0.00000000e+00  1.00000000e+00\n",
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      "[  1.           9.           0.           1.          31.\n",
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      "[  1.          26.           0.           1.          36.\n",
      " 117.           0.           2.           0.           0.\n",
      "   0.           0.           0.          33.           1.64302154] tensor(12596.2402)\n",
      "[2.00000000e+00 1.01800000e+03 0.00000000e+00 1.00000000e+00\n",
      " 3.00000000e+01 1.11000000e+02 0.00000000e+00 2.00000000e+00\n",
      " 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00\n",
      " 0.00000000e+00 3.30000000e+01 4.24233531e-01] tensor(7776.9434)\n",
      "[ 4.         45.          0.          1.         42.         86.\n",
      "  0.          0.          0.          0.          0.          0.\n",
      "  0.         30.          0.20047054] tensor(7288.6064)\n",
      "[ 3.00000000e+00  1.70300000e+03  0.00000000e+00  0.00000000e+00\n",
      "  3.40000000e+01  1.07000000e+02  0.00000000e+00  2.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  3.30000000e+01 -2.48496109e-02] tensor(6830.9341)\n",
      "[  8.           9.           0.           1.          31.\n",
      " 104.           0.           2.           0.           0.\n",
      "   0.           0.           0.          33.          -1.04358761] tensor(4859.0713)\n",
      "[  5.         159.           1.           1.          42.\n",
      "  86.           0.           0.           0.           0.\n",
      "   0.           0.           0.          30.           1.64302154] tensor(12596.2402)\n",
      "[  2.         160.           1.           1.          25.\n",
      " 110.           0.           2.           0.           0.\n",
      "   0.           0.           0.          21.           1.47629237] tensor(11384.8896)\n",
      "[  1.        407.          1.          1.         45.        126.\n",
      "   0.          2.          0.          0.          0.          0.\n",
      "   0.         31.          1.9010312] tensor(17077.3359)\n",
      "[  2.           9.           0.           1.          22.\n",
      " 113.           1.           0.           0.           0.\n",
      "   0.           0.           0.          30.          -1.04358761] tensor(4859.0713)\n",
      "[  1.         178.           0.           1.          40.\n",
      " 116.           0.           2.           3.           3.\n",
      "   0.           0.           0.          31.           1.20889385] tensor(10080.1406)\n",
      "[ 2.00000000e+00  5.54000000e+02  1.00000000e+00  1.00000000e+00\n",
      "  2.80000000e+01  1.15000000e+02  1.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  1.40000000e+01 -4.59278471e-01] tensor(6000.)\n",
      "[ 1.00000000e+00  7.30000000e+02  0.00000000e+00  1.00000000e+00\n",
      "  3.00000000e+01  1.20000000e+02  0.00000000e+00  2.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  3.30000000e+01 -5.11043371e-01] tensor(5902.6431)\n",
      "[ 1.00000000e+00  7.49000000e+02  0.00000000e+00  1.00000000e+00\n",
      "  3.40000000e+01  1.13000000e+02  0.00000000e+00  2.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  2.60000000e+01 -7.06774568e-01] tensor(5531.9990)\n",
      "[ 1.00000000e+00  8.42000000e+02  0.00000000e+00  1.00000000e+00\n",
      "  3.00000000e+01  1.20000000e+02  0.00000000e+00  2.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  3.10000000e+01 -5.11043371e-01] tensor(5902.6431)\n",
      "[  1.        552.          0.          1.         28.        113.\n",
      "   1.          0.          0.          0.          0.          0.\n",
      "   0.         17.          1.2775747] tensor(10369.2578)\n",
      "[ 4.00000000e+00  1.70300000e+03  0.00000000e+00  0.00000000e+00\n",
      "  3.10000000e+01  1.04000000e+02  1.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  3.10000000e+01 -1.29818526e+00] tensor(4268.)\n",
      "[  2.         852.           0.           1.          30.\n",
      " 114.           1.           0.           0.           0.\n",
      "   0.           0.           0.          25.          -1.18132525] tensor(4553.9561)\n",
      "[  1.         554.           1.           1.          42.\n",
      "  86.           0.           0.           0.           0.\n",
      "   0.           0.           0.          33.           1.96929153] tensor(26675.)\n",
      "[  2.         757.           0.           1.          31.\n",
      " 117.           1.           0.           0.           0.\n",
      "   0.           0.           0.          20.          -1.18132525] tensor(4553.9561)\n",
      "[ 1.00000000e+00  1.70300000e+03  0.00000000e+00  0.00000000e+00\n",
      "  3.80000000e+01  1.12000000e+02  0.00000000e+00  2.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  3.10000000e+01 -2.46441106e-01] tensor(6402.)\n",
      "[  2.         749.           0.           1.          30.\n",
      " 114.           1.           0.           0.           0.\n",
      "   0.           0.           0.          33.          -1.04358761] tensor(4859.0713)\n",
      "[ 2.00000000e+00  1.70300000e+03  0.00000000e+00  0.00000000e+00\n",
      "  3.60000000e+01  1.19000000e+02  1.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  3.30000000e+01 -2.48496109e-02] tensor(6830.9341)\n",
      "[  1.         543.           0.           1.          31.\n",
      " 118.           0.           2.           0.           0.\n",
      "   0.           0.           0.          33.          -1.18132525] tensor(4553.9561)\n",
      "[  2.         160.           1.           1.          32.\n",
      " 118.           0.           2.           0.           0.\n",
      "   0.           0.           0.          26.           0.42423353] tensor(7776.9434)\n",
      "[  2.          49.           0.           1.          30.\n",
      " 120.           1.           0.           0.           0.\n",
      "   0.           0.           0.          33.           0.20047054] tensor(7288.6064)\n",
      "[ 2.00000000e+00  7.48000000e+02  0.00000000e+00  1.00000000e+00\n",
      "  3.80000000e+01  1.14000000e+02  1.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  3.30000000e+01 -2.46441106e-01] tensor(6402.)\n",
      "[ 1.00000000e+00  1.70300000e+03  0.00000000e+00  0.00000000e+00\n",
      "  4.10000000e+01  1.23000000e+02  0.00000000e+00  2.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  3.30000000e+01 -1.39501774e+00] tensor(4000.)\n",
      "[  1.         652.           0.           1.          44.\n",
      " 129.           0.           2.           0.           0.\n",
      "   0.           0.           0.          33.          -1.29818526] tensor(4268.)\n",
      "[1.00000000e+00 7.19000000e+02 0.00000000e+00 1.00000000e+00\n",
      " 3.90000000e+01 1.16000000e+02 0.00000000e+00 2.00000000e+00\n",
      " 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00\n",
      " 0.00000000e+00 3.10000000e+01 2.00470543e-01] tensor(7288.6064)\n",
      "[ 1.00000000e+00  7.53000000e+02  0.00000000e+00  1.00000000e+00\n",
      "  3.10000000e+01  1.17000000e+02  0.00000000e+00  2.00000000e+00\n",
      "  3.00000000e+00  3.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  3.30000000e+01 -7.06774568e-01] tensor(5531.9990)\n",
      "[  2.         407.           1.           1.          23.\n",
      " 113.           1.           0.           0.           0.\n",
      "   0.           0.           0.          33.           0.93187116] tensor(9107.9121)\n",
      "[  2.         852.           0.           1.          28.\n",
      " 104.           1.           0.           0.           0.\n",
      "   0.           0.           0.          33.          -1.04358761] tensor(4859.0713)\n",
      "[  2.          54.           0.           1.          36.\n",
      " 119.           0.           2.           0.           0.\n",
      "   0.           0.           0.          33.          -0.70677457] tensor(5531.9990)\n",
      "[  2.         310.           0.           1.          34.\n",
      " 113.           0.           2.           0.           0.\n",
      "   0.           0.           0.          33.          -1.29818526] tensor(4268.)\n",
      "[  2.         870.           0.           1.          42.\n",
      "  86.           0.           0.           0.           0.\n",
      "   0.           0.           0.          30.           1.94012006] tensor(19442.3574)\n",
      "[  2.         734.           1.           1.          42.\n",
      "  86.           0.           0.           0.           0.\n",
      "   0.           0.           0.          33.           0.99069543] tensor(9293.8887)\n",
      "[ 2.00000000e+00  1.70300000e+03  0.00000000e+00  0.00000000e+00\n",
      "  3.10000000e+01  1.17000000e+02  1.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  3.30000000e+01 -1.04358761e+00] tensor(4859.0713)\n",
      "[  2.         652.           0.           1.          28.\n",
      " 115.           0.           2.           0.           0.\n",
      "   0.           0.           0.          30.           1.49124956] tensor(11476.1299)\n",
      "[4.00000000e+00 1.70300000e+03 0.00000000e+00 0.00000000e+00\n",
      " 4.20000000e+01 8.60000000e+01 0.00000000e+00 0.00000000e+00\n",
      " 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00\n",
      " 0.00000000e+00 2.30000000e+01 5.87419996e-01] tensor(8163.3535)\n",
      "[2.00000000e+00 1.70300000e+03 0.00000000e+00 0.00000000e+00\n",
      " 3.10000000e+01 1.19000000e+02 1.00000000e+00 0.00000000e+00\n",
      " 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00\n",
      " 0.00000000e+00 2.60000000e+01 1.47629237e+00] tensor(11384.8896)\n",
      "[  1.         652.           0.           1.          31.\n",
      " 121.           0.           2.           3.           3.\n",
      "   0.           0.           0.          33.           1.92387304] tensor(18221.5156)\n",
      "[2.00000000e+00 1.24500000e+03 0.00000000e+00 1.00000000e+00\n",
      " 3.00000000e+01 1.03000000e+02 0.00000000e+00 2.00000000e+00\n",
      " 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00\n",
      " 0.00000000e+00 2.70000000e+01 3.68223674e-01] tensor(7650.7529)\n",
      "[ 2.00000000e+00  1.70300000e+03  0.00000000e+00  0.00000000e+00\n",
      "  3.60000000e+01  1.00000000e+02  1.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  5.00000000e+00 -1.18132525e+00] tensor(4553.9561)\n",
      "[ 3.          9.          0.          1.         42.         86.\n",
      "  0.          0.          0.          0.          0.          0.\n",
      "  0.         33.         -1.18132525] tensor(4553.9561)\n",
      "[  1.         160.           1.           1.          42.\n",
      "  86.           0.           0.           0.           0.\n",
      "   0.           0.           0.          28.          -1.18132525] tensor(4553.9561)\n",
      "[ 2.00000000e+00  8.70000000e+02  0.00000000e+00  1.00000000e+00\n",
      "  4.30000000e+01  1.25000000e+02  1.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  3.30000000e+01 -5.11043371e-01] tensor(5902.6431)\n",
      "[  1.         652.           0.           1.          42.\n",
      "  86.           0.           0.           0.           0.\n",
      "   0.           0.           0.          15.           0.84684595] tensor(8853.9639)\n",
      "[2.00000000e+00 1.70300000e+03 0.00000000e+00 0.00000000e+00\n",
      " 3.70000000e+01 1.21000000e+02 1.00000000e+00 0.00000000e+00\n",
      " 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00\n",
      " 0.00000000e+00 3.30000000e+01 1.64302154e+00] tensor(12596.2402)\n",
      "[2.0000000e+00 7.4700000e+02 0.0000000e+00 1.0000000e+00 2.8000000e+01\n",
      " 1.1300000e+02 1.0000000e+00 0.0000000e+00 0.0000000e+00 0.0000000e+00\n",
      " 0.0000000e+00 0.0000000e+00 0.0000000e+00 3.3000000e+01 5.1998844e-01] tensor(8000.)\n",
      "[  2.         311.           0.           1.          30.\n",
      " 114.           1.           0.           0.           0.\n",
      "   0.           0.           0.          33.           0.51998844] tensor(8000.)\n",
      "[3.00000000e+00 1.70300000e+03 0.00000000e+00 0.00000000e+00\n",
      " 2.60000000e+01 1.06000000e+02 1.00000000e+00 0.00000000e+00\n",
      " 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00\n",
      " 0.00000000e+00 3.00000000e+01 2.00470543e-01] tensor(7288.6064)\n",
      "[ 1.00000000e+00  7.34000000e+02  1.00000000e+00  1.00000000e+00\n",
      "  3.40000000e+01  1.13000000e+02  0.00000000e+00  2.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  3.30000000e+01 -5.11043371e-01] tensor(5902.6431)\n",
      "[  1.         652.           0.           1.          31.\n",
      " 121.           0.           2.           3.           3.\n",
      "   0.           0.           0.          29.           1.82760652] tensor(15000.)\n",
      "[  2.         748.           0.           1.          27.\n",
      " 115.           0.           2.           0.           0.\n",
      "   0.           0.           0.          33.           1.34300582] tensor(10670.)\n",
      "[  2.         712.           0.           1.          42.\n",
      "  86.           0.           0.           0.           0.\n",
      "   0.           0.           0.          33.           1.92387304] tensor(18221.5156)\n",
      "[2.00000000e+00 6.49000000e+02 0.00000000e+00 1.00000000e+00\n",
      " 4.20000000e+01 8.60000000e+01 0.00000000e+00 0.00000000e+00\n",
      " 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00\n",
      " 0.00000000e+00 2.20000000e+01 6.41262404e-01] tensor(8297.9980)\n",
      "[  2.          58.           0.           1.          23.\n",
      " 113.           1.           0.           0.           0.\n",
      "   0.           0.           0.          30.          -0.45927847] tensor(6000.)\n",
      "[  2.         840.           0.           1.          23.\n",
      " 113.           1.           0.           0.           0.\n",
      "   0.           0.           0.          33.          -1.04358761] tensor(4859.0713)\n",
      "[  3.         734.           1.           1.          42.\n",
      "  86.           0.           0.           0.           0.\n",
      "   0.           0.           0.          31.           1.64302154] tensor(12596.2402)\n",
      "[ 1.00000000e+00  1.70300000e+03  0.00000000e+00  0.00000000e+00\n",
      "  2.80000000e+01  1.12000000e+02  0.00000000e+00  2.00000000e+00\n",
      "  3.00000000e+00  3.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  3.00000000e+00  3.30000000e+01 -4.59278471e-01] tensor(6000.)\n",
      "[  1.         489.           0.           1.          34.\n",
      " 112.           0.           2.           0.           0.\n",
      "   0.           0.           0.          18.          -1.18132525] tensor(4553.9561)\n",
      "[  2.         159.           1.           1.          28.\n",
      " 116.           0.           2.           0.           0.\n",
      "   0.           0.           0.          29.          -0.70677457] tensor(5531.9990)\n",
      "[ 4.00000000e+00  3.36000000e+02  0.00000000e+00  1.00000000e+00\n",
      "  2.70000000e+01  1.11000000e+02  0.00000000e+00  2.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  3.30000000e+01 -8.13051736e-02] tensor(6720.0938)\n",
      "[  3.        554.          1.          1.         42.         86.\n",
      "   0.          0.          0.          0.          0.          0.\n",
      "   0.         27.          0.6412624] tensor(8297.9980)\n",
      "[  1.         749.           0.           1.          29.\n",
      " 106.           0.           2.           0.           0.\n",
      "   0.           0.           0.          33.           1.82760652] tensor(15000.)\n",
      "[ 1.00000000e+00  8.51000000e+02  0.00000000e+00  1.00000000e+00\n",
      "  2.90000000e+01  1.06000000e+02  0.00000000e+00  2.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  3.30000000e+01 -4.59278471e-01] tensor(6000.)\n",
      "[  2.         653.           0.           1.          50.\n",
      " 127.           0.           2.           0.           0.\n",
      "   0.           0.           0.           7.           1.68158211] tensor(12961.5723)\n",
      "[  2.         160.           1.           1.          30.\n",
      " 120.           0.           2.           0.           0.\n",
      "   0.           0.           0.          33.          -1.29818526] tensor(4268.)\n",
      "[  1.           9.           0.           1.          30.\n",
      " 114.           0.           2.           3.           3.\n",
      "   0.           0.           0.          33.          -1.39501774] tensor(4000.)\n",
      "[  2.         311.           0.           1.          39.\n",
      " 116.           1.           0.           0.           0.\n",
      "   0.           0.           0.          31.          -0.88503262] tensor(5184.6289)\n",
      "[1.00000000e+00 1.70300000e+03 0.00000000e+00 0.00000000e+00\n",
      " 4.20000000e+01 8.60000000e+01 0.00000000e+00 0.00000000e+00\n",
      " 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00\n",
      " 0.00000000e+00 3.30000000e+01 1.34300582e+00] tensor(10670.)\n",
      "[  1.         230.           0.           1.          39.\n",
      " 116.           0.           2.           3.           3.\n",
      "   0.           0.           3.          33.          -0.45927847] tensor(6000.)\n",
      "[2.00000000e+00 1.70300000e+03 0.00000000e+00 0.00000000e+00\n",
      " 2.30000000e+01 1.13000000e+02 0.00000000e+00 2.00000000e+00\n",
      " 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00\n",
      " 0.00000000e+00 3.00000000e+01 4.24233531e-01] tensor(7776.9434)\n",
      "[  1.         159.           1.           1.          42.\n",
      "  86.           0.           0.           0.           0.\n",
      "   0.           0.           0.          25.           0.93187116] tensor(9107.9121)\n",
      "[  2.         840.           0.           1.          30.\n",
      " 118.           1.           0.           0.           0.\n",
      "   0.           0.           0.          31.          -1.18132525] tensor(4553.9561)\n",
      "[ 1.00000000e+00  5.52000000e+02  0.00000000e+00  1.00000000e+00\n",
      "  3.50000000e+01  1.19000000e+02  1.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  3.30000000e+01 -8.13051736e-02] tensor(6720.0938)\n",
      "[ 1.00000000e+00  1.70300000e+03  0.00000000e+00  0.00000000e+00\n",
      "  3.20000000e+01  1.18000000e+02  0.00000000e+00  2.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  3.10000000e+01 -1.18132525e+00] tensor(4553.9561)\n",
      "[ 2.00000000e+00  1.63000000e+03  0.00000000e+00  0.00000000e+00\n",
      "  3.40000000e+01  1.09000000e+02  0.00000000e+00  2.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  3.30000000e+01 -2.46441106e-01] tensor(6402.)\n",
      "[  1.         160.           1.           1.          35.\n",
      " 113.           0.           2.           0.           0.\n",
      "   0.           0.           0.          33.          -1.18132525] tensor(4553.9561)\n",
      "[  2.           9.           0.           1.          37.\n",
      " 112.           1.           0.           0.           0.\n",
      "   0.           0.           0.          16.          -0.70677457] tensor(5531.9990)\n",
      "[  2.         629.           0.           1.          42.\n",
      "  86.           0.           0.           0.           0.\n",
      "   0.           0.           0.          30.           1.03704191] tensor(9447.1797)\n",
      "[  1.         729.           0.           1.          32.\n",
      " 118.           0.           2.           3.           3.\n",
      "   0.           0.           0.          26.           1.64302154] tensor(12596.2402)\n",
      "[  1.         554.           1.           1.          28.\n",
      " 112.           0.           2.           0.           0.\n",
      "   0.           0.           0.          33.           0.84684595] tensor(8853.9639)\n",
      "[  2.         814.           0.           1.          30.\n",
      " 108.           1.           0.           0.           0.\n",
      "   0.           0.           0.          33.          -1.04358761] tensor(4859.0713)\n",
      "[  2.          54.           0.           1.          31.\n",
      " 104.           1.           0.           0.           0.\n",
      "   0.           0.           0.          31.          -1.39501774] tensor(4000.)\n",
      "[ 1.00000000e+00  6.52000000e+02  0.00000000e+00  1.00000000e+00\n",
      "  3.40000000e+01  1.08000000e+02  0.00000000e+00  2.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  3.10000000e+01 -5.11043371e-01] tensor(5902.6431)\n",
      "[  2.         852.           0.           1.          31.\n",
      " 117.           0.           2.           0.           0.\n",
      "   0.           0.           0.          33.          -1.39501774] tensor(4000.)\n",
      "[ 2.00000000e+00  1.63000000e+03  0.00000000e+00  0.00000000e+00\n",
      "  3.40000000e+01  1.13000000e+02  1.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  3.30000000e+01 -1.04358761e+00] tensor(4859.0713)\n",
      "[  2.         238.           0.           1.          42.\n",
      "  86.           0.           0.           0.           0.\n",
      "   0.           0.           0.          33.          -0.70677457] tensor(5531.9990)\n",
      "[  1.         407.           1.           1.          28.\n",
      " 112.           0.           2.           0.           0.\n",
      "   0.           0.           0.          33.           0.73256683] tensor(8536.)\n",
      "[ 2.00000000e+00  1.70300000e+03  0.00000000e+00  0.00000000e+00\n",
      "  4.50000000e+01  1.26000000e+02  1.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  3.10000000e+01 -2.48496109e-02] tensor(6830.9341)\n",
      "[  1.         407.           1.           1.          37.\n",
      " 114.           0.           2.           0.           0.\n",
      "   0.           0.           0.          33.          -1.04358761] tensor(4859.0713)\n",
      "[  1.         837.           0.           1.          30.\n",
      " 119.           0.           2.           0.           0.\n",
      "   0.           0.           0.          31.           1.75628398] tensor(13829.9971)\n",
      "[2.00000000e+00 1.45000000e+03 0.00000000e+00 1.00000000e+00\n",
      " 4.20000000e+01 8.60000000e+01 0.00000000e+00 0.00000000e+00\n",
      " 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00\n",
      " 0.00000000e+00 2.90000000e+01 4.24233531e-01] tensor(7776.9434)\n",
      "[  1.         159.           1.           1.          42.\n",
      "  86.           0.           0.           0.           0.\n",
      "   0.           0.           0.          33.           0.20047054] tensor(7288.6064)\n",
      "[  1.         652.           0.           1.          39.\n",
      " 116.           0.           2.           3.           3.\n",
      "   0.           0.           0.          31.           1.96413774] tensor(23617.9492)\n",
      "[  2.         160.           1.           1.          39.\n",
      " 117.           1.           0.           0.           0.\n",
      "   0.           0.           0.          30.          -0.70677457] tensor(5531.9990)\n",
      "[ 2.00000000e+00  6.52000000e+02  0.00000000e+00  1.00000000e+00\n",
      "  4.20000000e+01  8.60000000e+01  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  3.30000000e+01 -5.11043371e-01] tensor(5902.6431)\n",
      "[  1.         160.           1.           1.          39.\n",
      " 121.           0.           2.           0.           0.\n",
      "   0.           0.           0.          24.           1.34300582] tensor(10670.)\n",
      "[ 2.00000000e+00  8.40000000e+02  0.00000000e+00  1.00000000e+00\n",
      "  3.40000000e+01  1.08000000e+02  1.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  3.30000000e+01 -7.06774568e-01] tensor(5531.9990)\n",
      "[1.20000000e+01 2.89000000e+02 0.00000000e+00 1.00000000e+00\n",
      " 3.60000000e+01 1.17000000e+02 0.00000000e+00 2.00000000e+00\n",
      " 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00\n",
      " 0.00000000e+00 3.30000000e+01 1.43569229e-01] tensor(7170.3403)\n",
      "[  2.         771.           0.           1.          30.\n",
      " 104.           1.           0.           0.           0.\n",
      "   0.           0.           0.          31.           1.96709287] tensor(25000.)\n",
      "[ 1.00000000e+00  5.54000000e+02  1.00000000e+00  1.00000000e+00\n",
      "  3.60000000e+01  1.20000000e+02  0.00000000e+00  2.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  3.30000000e+01 -2.46441106e-01] tensor(6402.)\n",
      "[1.00000000e+00 4.07000000e+02 1.00000000e+00 1.00000000e+00\n",
      " 4.30000000e+01 1.25000000e+02 0.00000000e+00 2.00000000e+00\n",
      " 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00\n",
      " 0.00000000e+00 3.30000000e+01 2.00470543e-01] tensor(7288.6064)\n",
      "[1.00000000e+00 8.37000000e+02 0.00000000e+00 1.00000000e+00\n",
      " 3.90000000e+01 1.16000000e+02 0.00000000e+00 2.00000000e+00\n",
      " 3.00000000e+00 3.00000000e+00 0.00000000e+00 0.00000000e+00\n",
      " 0.00000000e+00 3.10000000e+01 2.00470543e-01] tensor(7288.6064)\n",
      "[  2.         840.           0.           1.          42.\n",
      "  86.           0.           0.           0.           0.\n",
      "   0.           0.           0.          29.           0.99069543] tensor(9293.8887)\n",
      "[  2.         285.           0.           1.          34.\n",
      " 108.           0.           2.           0.           0.\n",
      "   0.           0.           0.          33.          -0.70677457] tensor(5531.9990)\n",
      "[  1.         747.           0.           1.          31.\n",
      " 119.           0.           2.           0.           0.\n",
      "   0.           0.           0.           6.           1.20889385] tensor(10080.1406)\n",
      "[ 1.00000000e+00  9.44000000e+02  0.00000000e+00  1.00000000e+00\n",
      "  3.00000000e+01  1.14000000e+02  0.00000000e+00  2.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  3.30000000e+01 -5.11043371e-01] tensor(5902.6431)\n",
      "[ 12.         840.           0.           1.          42.\n",
      "  86.           0.           0.           0.           0.\n",
      "   0.           0.           0.          22.           0.93187116] tensor(9107.9121)\n",
      "[1.0000000e+00 5.5400000e+02 1.0000000e+00 1.0000000e+00 3.9000000e+01\n",
      " 1.2100000e+02 0.0000000e+00 2.0000000e+00 0.0000000e+00 0.0000000e+00\n",
      " 0.0000000e+00 0.0000000e+00 0.0000000e+00 3.1000000e+01 5.1998844e-01] tensor(8000.)\n",
      "[ 2.00000000e+00  1.70300000e+03  0.00000000e+00  0.00000000e+00\n",
      "  2.30000000e+01  1.13000000e+02  1.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  3.00000000e+01 -1.29818526e+00] tensor(4268.)\n",
      "[ 1.00000000e+00  8.42000000e+02  0.00000000e+00  1.00000000e+00\n",
      "  3.90000000e+01  1.16000000e+02  0.00000000e+00  2.00000000e+00\n",
      "  3.00000000e+00  3.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  3.00000000e+00  3.10000000e+01 -8.13051736e-02] tensor(6720.0938)\n",
      "[ 1.00000000e+00  4.89000000e+02  0.00000000e+00  1.00000000e+00\n",
      "  3.40000000e+01  1.13000000e+02  0.00000000e+00  2.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  3.30000000e+01 -3.01143857e-01] tensor(6298.1201)\n",
      "[  1.         652.           0.           1.          27.\n",
      " 112.           0.           2.           0.           0.\n",
      "   0.           0.           0.          30.           0.73256683] tensor(8536.)\n",
      "[  2.         734.           1.           1.          41.\n",
      " 123.           0.           2.           0.           0.\n",
      "   0.           0.           0.          33.          -1.18132525] tensor(4553.9561)\n",
      "[ 1.00000000e+00  1.70300000e+03  0.00000000e+00  0.00000000e+00\n",
      "  4.20000000e+01  8.60000000e+01  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  3.30000000e+01 -3.01143857e-01] tensor(6298.1201)\n",
      "[  1.         230.           0.           1.          25.\n",
      " 102.           0.           2.           0.           0.\n",
      "   0.           0.           0.          33.          -0.88503262] tensor(5184.6289)\n",
      "[  1.         843.           0.           1.          34.\n",
      " 113.           0.           2.           0.           0.\n",
      "   0.           0.           0.          33.           1.72544904] tensor(13440.1875)\n",
      "[ 2.00000000e+00  8.52000000e+02  0.00000000e+00  1.00000000e+00\n",
      "  4.20000000e+01  8.60000000e+01  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  3.30000000e+01 -7.06774568e-01] tensor(5531.9990)\n",
      "[1.00000000e+00 4.07000000e+02 1.00000000e+00 1.00000000e+00\n",
      " 3.20000000e+01 1.12000000e+02 0.00000000e+00 2.00000000e+00\n",
      " 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00\n",
      " 0.00000000e+00 3.30000000e+01 2.00470543e-01] tensor(7288.6064)\n",
      "[  1.         729.           0.           1.          22.\n",
      " 113.           0.           2.           3.           3.\n",
      "   0.           0.           3.          33.           1.93654839] tensor(19126.8828)\n",
      "[2.00000000e+00 1.70300000e+03 0.00000000e+00 0.00000000e+00\n",
      " 4.20000000e+01 8.60000000e+01 0.00000000e+00 0.00000000e+00\n",
      " 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00\n",
      " 0.00000000e+00 3.00000000e+01 5.87419996e-01] tensor(8163.3535)\n",
      "[  1.         840.           0.           1.          30.\n",
      " 112.           0.           2.           0.           0.\n",
      "   0.           0.           0.          33.          -0.88503262] tensor(5184.6289)\n",
      "[ 1.00000000e+00  1.70300000e+03  0.00000000e+00  0.00000000e+00\n",
      "  2.80000000e+01  1.04000000e+02  0.00000000e+00  2.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  2.70000000e+01 -3.01143857e-01] tensor(6298.1201)\n",
      "[ 3.00000000e+00  9.44000000e+02  0.00000000e+00  1.00000000e+00\n",
      "  4.20000000e+01  8.60000000e+01  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  3.10000000e+01 -8.85032618e-01] tensor(5184.6289)\n",
      "[ 1.20000000e+01  6.50000000e+02  0.00000000e+00  0.00000000e+00\n",
      "  3.40000000e+01  1.08000000e+02  0.00000000e+00  2.00000000e+00\n",
      "  3.00000000e+00  3.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  3.10000000e+01 -8.13051736e-02] tensor(6720.0938)\n",
      "[  1.         944.           0.           1.          34.\n",
      " 108.           0.           2.           0.           0.\n",
      "   0.           0.           0.          31.           1.97065282] tensor(28462.2246)\n",
      "[  2.         635.           0.           1.          42.\n",
      "  86.           0.           0.           0.           0.\n",
      "   0.           0.           0.          31.          -0.70677457] tensor(5531.9990)\n",
      "[1.00000000e+00 1.24500000e+03 0.00000000e+00 1.00000000e+00\n",
      " 2.70000000e+01 1.12000000e+02 0.00000000e+00 2.00000000e+00\n",
      " 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00\n",
      " 0.00000000e+00 3.30000000e+01 1.92133125e+00] tensor(18069.5098)\n",
      "[  1.         646.           0.           1.          30.\n",
      " 106.           0.           2.           0.           0.\n",
      "   0.           0.           0.          33.          -0.88503262] tensor(5184.6289)\n",
      "[  1.         160.           1.           1.          43.\n",
      " 126.           0.           2.           0.           0.\n",
      "   0.           0.           0.          33.          -1.39501774] tensor(4000.)\n",
      "[ 2.00000000e+00  1.70300000e+03  0.00000000e+00  0.00000000e+00\n",
      "  3.40000000e+01  1.15000000e+02  1.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  3.30000000e+01 -5.11043371e-01] tensor(5902.6431)\n",
      "[ 2.00000000e+00  1.70300000e+03  0.00000000e+00  0.00000000e+00\n",
      "  3.40000000e+01  1.08000000e+02  1.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  3.30000000e+01 -5.11043371e-01] tensor(5902.6431)\n",
      "[  2.         772.           0.           1.          30.\n",
      " 114.           1.           0.           0.           0.\n",
      "   0.           0.           0.          33.           1.96709287] tensor(25000.)\n",
      "[ 3.00000000e+00  9.44000000e+02  0.00000000e+00  1.00000000e+00\n",
      "  4.20000000e+01  8.60000000e+01  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  3.30000000e+01 -7.06774568e-01] tensor(5531.9990)\n",
      "[1.00000000e+00 6.52000000e+02 0.00000000e+00 1.00000000e+00\n",
      " 3.90000000e+01 1.17000000e+02 0.00000000e+00 2.00000000e+00\n",
      " 3.00000000e+00 3.00000000e+00 0.00000000e+00 0.00000000e+00\n",
      " 3.00000000e+00 2.20000000e+01 2.00470543e-01] tensor(7288.6064)\n",
      "[ 2.00000000e+00  8.52000000e+02  0.00000000e+00  1.00000000e+00\n",
      "  2.90000000e+01  1.05000000e+02  0.00000000e+00  2.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  6.00000000e+00 -5.11043371e-01] tensor(5902.6431)\n",
      "[  2.        840.          0.          1.         44.        129.\n",
      "   1.          0.          0.          0.          0.          0.\n",
      "   0.         33.          1.2775747] tensor(10369.2578)\n",
      "[  1.         635.           0.           1.          28.\n",
      " 112.           0.           2.           0.           0.\n",
      "   0.           0.           0.          31.           1.11436842] tensor(9718.1426)\n",
      "[1.00000000e+00 7.49000000e+02 0.00000000e+00 1.00000000e+00\n",
      " 3.70000000e+01 1.17000000e+02 0.00000000e+00 2.00000000e+00\n",
      " 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00\n",
      " 0.00000000e+00 3.10000000e+01 2.00470543e-01] tensor(7288.6064)\n",
      "[  2.         852.           0.           1.          31.\n",
      " 121.           1.           0.           0.           0.\n",
      "   0.           0.           0.          29.           1.11436842] tensor(9718.1426)\n",
      "[1.00000000e+00 8.65000000e+02 0.00000000e+00 1.00000000e+00\n",
      " 4.30000000e+01 1.26000000e+02 0.00000000e+00 2.00000000e+00\n",
      " 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00\n",
      " 0.00000000e+00 2.40000000e+01 5.87419996e-01] tensor(8163.3535)\n",
      "[ 1.00000000e+00  8.69000000e+02  0.00000000e+00  1.00000000e+00\n",
      "  3.30000000e+01  1.13000000e+02  0.00000000e+00  2.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  3.10000000e+01 -2.46441106e-01] tensor(6402.)\n",
      "[  2.         530.           0.           1.          28.\n",
      " 115.           0.           2.           0.           0.\n",
      "   0.           0.           0.          30.           1.92387304] tensor(18221.5156)\n",
      "[4.00000000e+00 1.70300000e+03 0.00000000e+00 0.00000000e+00\n",
      " 4.20000000e+01 8.60000000e+01 0.00000000e+00 0.00000000e+00\n",
      " 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00\n",
      " 0.00000000e+00 3.30000000e+01 1.43569229e-01] tensor(7170.3403)\n",
      "[  1.         151.           0.           1.          24.\n",
      " 118.           0.           2.           3.           3.\n",
      "   0.           0.           3.          21.           0.73256683] tensor(8536.)\n",
      "[  2.          60.           0.           1.          22.\n",
      " 108.           1.           0.           0.           0.\n",
      "   0.           0.           0.          30.          -1.04358761] tensor(4859.0713)\n",
      "[  2.         870.           0.           1.          42.\n",
      "  86.           0.           0.           0.           0.\n",
      "   0.           0.           0.          31.           1.11436842] tensor(9718.1426)\n",
      "[  2.         840.           0.           1.          29.\n",
      " 105.           1.           0.           0.           0.\n",
      "   0.           0.           0.          33.          -1.18132525] tensor(4553.9561)\n",
      "[1.00000000e+00 3.11000000e+02 0.00000000e+00 1.00000000e+00\n",
      " 3.00000000e+01 1.14000000e+02 0.00000000e+00 2.00000000e+00\n",
      " 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00\n",
      " 0.00000000e+00 3.30000000e+01 2.00470543e-01] tensor(7288.6064)\n",
      "[  2.         162.           0.           1.          26.\n",
      " 106.           0.           2.           0.           0.\n",
      "   0.           0.           0.          33.           1.34300582] tensor(10670.)\n",
      "[  1.          54.           0.           1.          30.\n",
      " 106.           0.           2.           0.           0.\n",
      "   0.           0.           0.          31.          -1.29818526] tensor(4268.)\n",
      "[ 2.00000000e+00  2.60000000e+01  0.00000000e+00  1.00000000e+00\n",
      "  3.60000000e+01  1.09000000e+02  0.00000000e+00  2.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  3.30000000e+01 -8.13051736e-02] tensor(6720.0938)\n",
      "[ 1.00000000e+00  1.70300000e+03  0.00000000e+00  0.00000000e+00\n",
      "  2.60000000e+01  1.17000000e+02  0.00000000e+00  2.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  3.30000000e+01 -1.39501774e+00] tensor(4000.)\n",
      "[ 2.00000000e+00  7.49000000e+02  0.00000000e+00  1.00000000e+00\n",
      "  3.10000000e+01  1.20000000e+02  1.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  2.60000000e+01 -4.59278471e-01] tensor(6000.)\n",
      "[2.00000000e+00 9.44000000e+02 0.00000000e+00 1.00000000e+00\n",
      " 4.20000000e+01 8.60000000e+01 0.00000000e+00 0.00000000e+00\n",
      " 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00\n",
      " 0.00000000e+00 1.60000000e+01 1.43569229e-01] tensor(7170.3403)\n",
      "[  2.         770.           0.           0.          35.\n",
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      "[  2.         852.           0.           1.          42.\n",
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      "[  2.         489.           0.           1.          34.\n",
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      "[ 2.00000000e+00  4.89000000e+02  0.00000000e+00  1.00000000e+00\n",
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      "[  1.         543.           0.           1.          29.\n",
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      "[  2.         841.           0.           1.          31.\n",
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      "[  2.         162.           0.           1.          30.\n",
      " 104.           1.           0.           0.           0.\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "   0.           0.           0.          31.           0.20047054] tensor(7288.6064)\n",
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      "[  2.         310.           0.           1.          30.\n",
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      "[  1.         160.           1.           1.          42.\n",
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      "[  2.        257.          1.          1.         39.        116.\n",
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      "[  2.         840.           0.           1.          30.\n",
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      "[ 12.         329.           0.           1.          36.\n",
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      "[  2.         554.           1.           1.          31.\n",
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      "[  4.        637.          0.          0.         42.         86.\n",
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      "[  1.      554.        1.        1.       26.      119.        0.\n",
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      "[  5.         159.           1.           1.          23.\n",
      " 113.           0.           2.           0.           0.\n",
      "   0.           0.           0.          30.           1.36054634] tensor(10755.5107)\n",
      "[ 1.00000000e+00  7.57000000e+02  0.00000000e+00  1.00000000e+00\n",
      "  3.90000000e+01  1.17000000e+02  0.00000000e+00  2.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  3.10000000e+01 -4.59278471e-01] tensor(6000.)\n",
      "[  1.         159.           1.           1.          31.\n",
      " 120.           0.           2.           3.           3.\n",
      "   0.           0.           0.          29.           0.84684595] tensor(8853.9639)\n",
      "[  1.         162.           0.           1.          36.\n",
      " 119.           0.           2.           0.           0.\n",
      "   0.           0.           0.          33.           0.20047054] tensor(7288.6064)\n",
      "[2.00000000e+00 8.53000000e+02 0.00000000e+00 1.00000000e+00\n",
      " 4.20000000e+01 8.60000000e+01 0.00000000e+00 0.00000000e+00\n",
      " 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00\n",
      " 0.00000000e+00 3.30000000e+01 4.24233531e-01] tensor(7776.9434)\n",
      "[ 1.00000000e+00  7.48000000e+02  0.00000000e+00  1.00000000e+00\n",
      "  3.00000000e+01  1.12000000e+02  0.00000000e+00  2.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  3.30000000e+01 -8.13051736e-02] tensor(6720.0938)\n",
      "[  2.         734.           1.           1.          42.\n",
      "  86.           0.           0.           0.           0.\n",
      "   0.           0.           0.          29.          -1.39501774] tensor(4000.)\n",
      "[  1.         160.           1.           1.          31.\n",
      " 104.           0.           2.           0.           0.\n",
      "   0.           0.           0.          28.           1.64302154] tensor(12596.2402)\n",
      "[  2.         712.           0.           1.          42.\n",
      "  86.           0.           0.           0.           0.\n",
      "   0.           0.           0.          27.          -0.88503262] tensor(5184.6289)\n",
      "[   3.         1703.            0.            0.           42.\n",
      "   86.            0.            0.            0.            0.\n",
      "    0.            0.            0.           29.            1.81503227] tensor(14756.6074)\n",
      "[ 2.00000000e+00  9.44000000e+02  0.00000000e+00  1.00000000e+00\n",
      "  2.30000000e+01  1.13000000e+02  1.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  3.00000000e+01 -2.48496109e-02] tensor(6830.9341)\n",
      "[  1.         289.           0.           1.          25.\n",
      " 118.           0.           2.           0.           0.\n",
      "   0.           0.           0.          33.           0.42423353] tensor(7776.9434)\n",
      "[  1.         714.           0.           1.          32.\n",
      " 118.           0.           2.           0.           0.\n",
      "   0.           0.           0.          26.          -1.29818526] tensor(4268.)\n",
      "[  1.         160.           1.           1.          32.\n",
      " 118.           0.           2.           0.           0.\n",
      "   0.           0.           0.          31.           0.36822367] tensor(7650.7529)\n",
      "[  2.         734.           1.           1.          37.\n",
      " 121.           1.           0.           0.           0.\n",
      "   0.           0.           0.          33.          -1.29818526] tensor(4268.)\n",
      "[ 1.00000000e+00  7.49000000e+02  0.00000000e+00  1.00000000e+00\n",
      "  3.60000000e+01  1.17000000e+02  0.00000000e+00  2.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  3.10000000e+01 -2.46441106e-01] tensor(6402.)\n",
      "[1.10000000e+01 6.58000000e+02 0.00000000e+00 1.00000000e+00\n",
      " 4.20000000e+01 8.60000000e+01 0.00000000e+00 0.00000000e+00\n",
      " 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00\n",
      " 0.00000000e+00 2.40000000e+01 1.43569229e-01] tensor(7170.3403)\n",
      "[ 12.         348.           0.           1.          25.\n",
      " 103.           0.           2.           0.           0.\n",
      "   0.           0.           0.          31.          -0.70677457] tensor(5531.9990)\n",
      "[ 1.00000000e+00  4.41000000e+02  0.00000000e+00  0.00000000e+00\n",
      "  4.20000000e+01  8.60000000e+01  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  3.10000000e+01 -2.48496109e-02] tensor(6830.9341)\n",
      "[ 2.00000000e+00  1.70300000e+03  0.00000000e+00  0.00000000e+00\n",
      "  4.20000000e+01  8.60000000e+01  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  3.10000000e+01 -2.46441106e-01] tensor(6402.)\n",
      "[ 2.00000000e+00  1.70300000e+03  0.00000000e+00  0.00000000e+00\n",
      "  4.20000000e+01  8.60000000e+01  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  1.50000000e+01 -2.48496109e-02] tensor(6830.9341)\n",
      "[  1.         530.           0.           1.          34.\n",
      " 117.           0.           2.           0.           0.\n",
      "   0.           0.           0.          33.          -0.88503262] tensor(5184.6289)\n",
      "[ 2.00000000e+00  1.70300000e+03  0.00000000e+00  0.00000000e+00\n",
      "  3.20000000e+01  1.18000000e+02  1.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  2.50000000e+01 -4.59278471e-01] tensor(6000.)\n",
      "[  2.         734.           1.           1.          28.\n",
      " 116.           0.           2.           0.           0.\n",
      "   0.           0.           0.          30.           1.20889385] tensor(10080.1406)\n",
      "[ 12.         159.           1.           1.          39.\n",
      " 116.           0.           2.           0.           0.\n",
      "   0.           0.           0.          33.           1.84178959] tensor(15301.5059)\n",
      "[  1.         348.           0.           1.          39.\n",
      " 116.           1.           0.           0.           0.\n",
      "   0.           0.           0.          31.           1.86015571] tensor(15745.2998)\n",
      "[  7.        629.          0.          1.         31.        117.\n",
      "   0.          2.          3.          3.          0.          0.\n",
      "   0.         29.          1.2775747] tensor(10369.2578)\n",
      "[  3.         714.           0.           1.          30.\n",
      " 108.           1.           0.           0.           0.\n",
      "   0.           0.           0.          33.          -1.29818526] tensor(4268.)\n",
      "[  1.         734.           1.           1.          39.\n",
      " 116.           0.           2.           0.           0.\n",
      "   0.           0.           0.          33.          -0.88503262] tensor(5184.6289)\n",
      "[  1.         311.           0.           1.          43.\n",
      " 125.           0.           2.           3.           3.\n",
      "   0.           0.           0.          31.          -1.29818526] tensor(4268.)\n",
      "[  1.          10.           0.           1.          39.\n",
      " 117.           0.           2.           3.           3.\n",
      "   0.           0.           3.          33.          -0.45927847] tensor(6000.)\n",
      "[2.0000000e+00 1.7030000e+03 0.0000000e+00 0.0000000e+00 4.4000000e+01\n",
      " 1.2900000e+02 1.0000000e+00 0.0000000e+00 0.0000000e+00 0.0000000e+00\n",
      " 0.0000000e+00 0.0000000e+00 0.0000000e+00 1.5000000e+01 5.1998844e-01] tensor(8000.)\n",
      "[1.00000000e+00 7.48000000e+02 0.00000000e+00 1.00000000e+00\n",
      " 3.00000000e+01 1.17000000e+02 0.00000000e+00 2.00000000e+00\n",
      " 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00\n",
      " 0.00000000e+00 2.80000000e+01 1.43569229e-01] tensor(7170.3403)\n",
      "[ 12.         257.           1.           1.          31.\n",
      " 121.           0.           2.           3.           3.\n",
      "   4.           0.           3.          29.           1.95906438] tensor(22134.9102)\n",
      "[ 4.00000000e+00  1.70300000e+03  0.00000000e+00  0.00000000e+00\n",
      "  4.20000000e+01  8.60000000e+01  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  3.30000000e+01 -1.04358761e+00] tensor(4859.0713)\n",
      "[ 1.00000000e+00  7.64000000e+02  0.00000000e+00  1.00000000e+00\n",
      "  3.00000000e+01  1.14000000e+02  0.00000000e+00  2.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  3.00000000e+01 -2.46441106e-01] tensor(6402.)\n",
      "[  2.         236.           0.           1.          34.\n",
      " 109.           0.           2.           0.           0.\n",
      "   0.           0.           0.          33.          -1.29818526] tensor(4268.)\n",
      "[ 12.         373.           0.           1.          28.\n",
      " 115.           0.           2.           0.           0.\n",
      "   0.           0.           0.          33.           1.34300582] tensor(10670.)\n",
      "[  1.         160.           1.           1.          39.\n",
      " 121.           0.           2.           0.           0.\n",
      "   0.           0.           0.          33.          -0.24644111] tensor(6402.)\n",
      "[1.00000000e+00 6.52000000e+02 0.00000000e+00 1.00000000e+00\n",
      " 3.40000000e+01 1.08000000e+02 0.00000000e+00 2.00000000e+00\n",
      " 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00\n",
      " 0.00000000e+00 2.90000000e+01 3.68223674e-01] tensor(7650.7529)\n",
      "[ 2.00000000e+00  8.42000000e+02  0.00000000e+00  1.00000000e+00\n",
      "  4.20000000e+01  8.60000000e+01  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  2.90000000e+01 -2.48496109e-02] tensor(6830.9341)\n",
      "[2.00000000e+00 1.70300000e+03 0.00000000e+00 0.00000000e+00\n",
      " 3.90000000e+01 1.16000000e+02 0.00000000e+00 2.00000000e+00\n",
      " 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00\n",
      " 0.00000000e+00 3.10000000e+01 7.96297255e-01] tensor(8710.2979)\n",
      "[2.00000000e+00 1.70300000e+03 0.00000000e+00 0.00000000e+00\n",
      " 3.40000000e+01 1.05000000e+02 1.00000000e+00 0.00000000e+00\n",
      " 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00\n",
      " 0.00000000e+00 3.30000000e+01 1.86966682e+00] tensor(16005.)\n",
      "[  2.         754.           0.           1.          30.\n",
      " 114.           1.           0.           0.           0.\n",
      "   0.           0.           0.          33.          -1.04358761] tensor(4859.0713)\n",
      "[  2.         297.           0.           1.          42.\n",
      "  86.           0.           0.           0.           0.\n",
      "   0.           0.           0.          27.           1.42012124] tensor(11063.9980)\n",
      "[  2.         289.           0.           1.          40.\n",
      " 113.           0.           2.           0.           0.\n",
      "   0.           0.           0.          16.           0.42423353] tensor(7776.9434)\n",
      "[  1.         841.           0.           1.          37.\n",
      " 112.           0.           2.           0.           0.\n",
      "   0.           0.           0.          33.          -1.39501774] tensor(4000.)\n",
      "[  2.         159.           1.           1.          42.\n",
      "  86.           0.           0.           0.           0.\n",
      "   0.           0.           0.          30.          -0.88503262] tensor(5184.6289)\n",
      "[  2.         159.           1.           1.          26.\n",
      " 119.           0.           2.           0.           0.\n",
      "   0.           0.           0.          21.           1.42012124] tensor(11063.9980)\n",
      "[  1.         764.           0.           1.          42.\n",
      "  86.           0.           0.           0.           0.\n",
      "   0.           0.           0.          33.           1.58881165] tensor(12147.6777)\n",
      "[  2.         944.           0.           1.          34.\n",
      " 113.           1.           0.           0.           0.\n",
      "   0.           0.           0.          31.           1.58881165] tensor(12147.6777)\n",
      "[  2.         629.           0.           1.          23.\n",
      " 113.           1.           0.           0.           0.\n",
      "   0.           0.           0.          29.           0.84684595] tensor(8853.9639)\n",
      "[  2.         632.           0.           1.          34.\n",
      " 108.           1.           0.           0.           0.\n",
      "   0.           0.           0.          31.          -0.70677457] tensor(5531.9990)\n",
      "[  1.         250.           0.           0.          34.\n",
      " 108.           0.           2.           0.           0.\n",
      "   0.           0.           0.          33.          -1.18132525] tensor(4553.9561)\n",
      "[ 2.00000000e+00  8.52000000e+02  0.00000000e+00  1.00000000e+00\n",
      "  2.50000000e+01  1.02000000e+02  0.00000000e+00  2.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  3.30000000e+01 -4.59278471e-01] tensor(6000.)\n",
      "[  1.         734.           1.           1.          42.\n",
      "  86.           0.           0.           0.           0.\n",
      "   0.           0.           0.          29.          -0.88503262] tensor(5184.6289)\n",
      "[ 2.00000000e+00  1.70300000e+03  0.00000000e+00  0.00000000e+00\n",
      "  3.10000000e+01  1.18000000e+02  0.00000000e+00  2.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  3.30000000e+01 -8.85032618e-01] tensor(5184.6289)\n",
      "[2.00000000e+00 6.36000000e+02 0.00000000e+00 1.00000000e+00\n",
      " 2.80000000e+01 1.13000000e+02 1.00000000e+00 0.00000000e+00\n",
      " 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00\n",
      " 0.00000000e+00 3.10000000e+01 2.00470543e-01] tensor(7288.6064)\n",
      "[ 2.00000000e+00  7.34000000e+02  1.00000000e+00  1.00000000e+00\n",
      "  2.80000000e+01  1.05000000e+02  1.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  3.30000000e+01 -8.13051736e-02] tensor(6720.0938)\n",
      "[ 1.00000000e+00  6.29000000e+02  0.00000000e+00  1.00000000e+00\n",
      "  3.40000000e+01  1.08000000e+02  0.00000000e+00  2.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  3.30000000e+01 -4.59278471e-01] tensor(6000.)\n",
      "[  2.         151.           0.           1.          42.\n",
      "  86.           0.           0.           0.           0.\n",
      "   0.           0.           0.          33.           1.54171779] tensor(11805.2861)\n",
      "[ 11.         840.           0.           1.          42.\n",
      "  86.           0.           0.           0.           0.\n",
      "   0.           0.           0.          33.           1.49124956] tensor(11476.1299)\n",
      "[ 1.00000000e+00  1.61900000e+03  0.00000000e+00  1.00000000e+00\n",
      "  4.30000000e+01  1.26000000e+02  0.00000000e+00  2.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  3.10000000e+01 -7.06774568e-01] tensor(5531.9990)\n",
      "[  2.         160.           1.           1.          34.\n",
      " 108.           0.           2.           0.           0.\n",
      "   0.           0.           0.          33.           0.42423353] tensor(7776.9434)\n",
      "[  1.         311.           0.           1.          24.\n",
      " 102.           0.           2.           0.           0.\n",
      "   0.           0.           0.          26.          -1.39501774] tensor(4000.)\n",
      "[  2.         646.           0.           1.          43.\n",
      " 126.           0.           2.           0.           0.\n",
      "   0.           0.           0.          33.          -0.70677457] tensor(5531.9990)\n",
      "[  1.         311.           0.           1.          39.\n",
      " 116.           0.           2.           0.           0.\n",
      "   0.           0.           0.          31.           1.92387304] tensor(18221.5156)\n",
      "[  1.         407.           1.           1.          43.\n",
      " 125.           0.           2.           0.           0.\n",
      "   0.           0.           0.          31.           1.96413774] tensor(23617.9492)\n",
      "[ 1.00000000e+00  8.42000000e+02  0.00000000e+00  1.00000000e+00\n",
      "  2.90000000e+01  1.06000000e+02  0.00000000e+00  2.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  3.00000000e+01 -2.46441106e-01] tensor(6402.)\n",
      "[2.00000000e+00 4.07000000e+02 1.00000000e+00 1.00000000e+00\n",
      " 4.20000000e+01 8.60000000e+01 0.00000000e+00 0.00000000e+00\n",
      " 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00\n",
      " 0.00000000e+00 3.30000000e+01 2.00470543e-01] tensor(7288.6064)\n",
      "[  1.         840.           0.           1.          32.\n",
      " 117.           0.           2.           0.           0.\n",
      "   0.           0.           0.          20.           1.68158211] tensor(12961.5723)\n",
      "[ 12.         290.           0.           1.          42.\n",
      "  86.           0.           0.           0.           0.\n",
      "   0.           0.           0.          31.           1.95906438] tensor(22134.9102)\n",
      "[2.00000000e+00 8.39000000e+02 0.00000000e+00 1.00000000e+00\n",
      " 2.80000000e+01 1.12000000e+02 0.00000000e+00 2.00000000e+00\n",
      " 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00\n",
      " 0.00000000e+00 3.00000000e+01 1.43569229e-01] tensor(7170.3403)\n",
      "[  1.         753.           0.           1.          36.\n",
      " 114.           0.           2.           0.           0.\n",
      "   0.           0.           0.          33.          -0.88503262] tensor(5184.6289)\n",
      "[2.00000000e+00 1.70300000e+03 0.00000000e+00 0.00000000e+00\n",
      " 4.20000000e+01 8.60000000e+01 0.00000000e+00 0.00000000e+00\n",
      " 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00\n",
      " 0.00000000e+00 3.30000000e+01 1.58881165e+00] tensor(12147.6777)\n",
      "[1.00000000e+00 4.07000000e+02 1.00000000e+00 1.00000000e+00\n",
      " 3.40000000e+01 1.08000000e+02 0.00000000e+00 2.00000000e+00\n",
      " 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00\n",
      " 0.00000000e+00 3.00000000e+01 2.00470543e-01] tensor(7288.6064)\n",
      "[ 1.          9.          0.          1.         42.         86.\n",
      "  0.          0.          0.          0.          0.          0.\n",
      "  0.         33.          1.90885242] tensor(17420.5957)\n",
      "[  1.         297.           0.           1.          39.\n",
      " 117.           0.           2.           0.           0.\n",
      "   0.           0.           0.          31.           0.51998844] tensor(8000.)\n",
      "[1.00000000e+00 1.70300000e+03 0.00000000e+00 0.00000000e+00\n",
      " 4.20000000e+01 8.60000000e+01 0.00000000e+00 0.00000000e+00\n",
      " 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00\n",
      " 0.00000000e+00 3.30000000e+01 1.97065282e+00] tensor(28462.2246)\n",
      "[  2.         311.           0.           1.          45.\n",
      " 126.           0.           2.           0.           0.\n",
      "   0.           0.           0.          31.          -1.18132525] tensor(4553.9561)\n",
      "[4.00000000e+00 1.70300000e+03 0.00000000e+00 0.00000000e+00\n",
      " 4.20000000e+01 8.60000000e+01 0.00000000e+00 0.00000000e+00\n",
      " 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00\n",
      " 0.00000000e+00 3.00000000e+01 2.00470543e-01] tensor(7288.6064)\n"
     ]
    },
    {
     "ename": "KeyboardInterrupt",
     "evalue": "",
     "output_type": "error",
     "traceback": [
      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[1;31mKeyboardInterrupt\u001b[0m                         Traceback (most recent call last)",
      "\u001b[1;32m<ipython-input-4-877b91aae22f>\u001b[0m in \u001b[0;36m<module>\u001b[1;34m\u001b[0m\n\u001b[0;32m      1\u001b[0m \u001b[1;32mfor\u001b[0m \u001b[0mi\u001b[0m \u001b[1;32min\u001b[0m \u001b[0mdataset\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m----> 2\u001b[1;33m     \u001b[0mprint\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mi\u001b[0m\u001b[1;33m[\u001b[0m\u001b[1;36m0\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m,\u001b[0m\u001b[0mi\u001b[0m\u001b[1;33m[\u001b[0m\u001b[1;36m1\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m",
      "\u001b[1;32mD:\\softwares\\Anaconda3\\lib\\site-packages\\ipykernel\\iostream.py\u001b[0m in \u001b[0;36mwrite\u001b[1;34m(self, string)\u001b[0m\n\u001b[0;32m    398\u001b[0m             \u001b[0mis_child\u001b[0m \u001b[1;33m=\u001b[0m \u001b[1;33m(\u001b[0m\u001b[1;32mnot\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_is_master_process\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    399\u001b[0m             \u001b[1;31m# only touch the buffer in the IO thread to avoid races\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 400\u001b[1;33m             \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mpub_thread\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mschedule\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;32mlambda\u001b[0m \u001b[1;33m:\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_buffer\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mwrite\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mstring\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m    401\u001b[0m             \u001b[1;32mif\u001b[0m \u001b[0mis_child\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    402\u001b[0m                 \u001b[1;31m# newlines imply flush in subprocesses\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32mD:\\softwares\\Anaconda3\\lib\\site-packages\\ipykernel\\iostream.py\u001b[0m in \u001b[0;36mschedule\u001b[1;34m(self, f)\u001b[0m\n\u001b[0;32m    201\u001b[0m             \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_events\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mappend\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mf\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    202\u001b[0m             \u001b[1;31m# wake event thread (message content is ignored)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 203\u001b[1;33m             \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_event_pipe\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0msend\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;34mb''\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m    204\u001b[0m         \u001b[1;32melse\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    205\u001b[0m             \u001b[0mf\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32mD:\\softwares\\Anaconda3\\lib\\site-packages\\zmq\\sugar\\socket.py\u001b[0m in \u001b[0;36msend\u001b[1;34m(self, data, flags, copy, track, routing_id, group)\u001b[0m\n\u001b[0;32m    393\u001b[0m                                  copy_threshold=self.copy_threshold)\n\u001b[0;32m    394\u001b[0m             \u001b[0mdata\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mgroup\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mgroup\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 395\u001b[1;33m         \u001b[1;32mreturn\u001b[0m \u001b[0msuper\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mSocket\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0msend\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mdata\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mflags\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mflags\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mcopy\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mcopy\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mtrack\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mtrack\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m    396\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    397\u001b[0m     \u001b[1;32mdef\u001b[0m \u001b[0msend_multipart\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mmsg_parts\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mflags\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;36m0\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mcopy\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;32mTrue\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mtrack\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;32mFalse\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;33m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32mzmq/backend/cython/socket.pyx\u001b[0m in \u001b[0;36mzmq.backend.cython.socket.Socket.send\u001b[1;34m()\u001b[0m\n",
      "\u001b[1;32mzmq/backend/cython/socket.pyx\u001b[0m in \u001b[0;36mzmq.backend.cython.socket.Socket.send\u001b[1;34m()\u001b[0m\n",
      "\u001b[1;32mzmq/backend/cython/socket.pyx\u001b[0m in \u001b[0;36mzmq.backend.cython.socket._send_copy\u001b[1;34m()\u001b[0m\n",
      "\u001b[1;32mD:\\softwares\\Anaconda3\\lib\\site-packages\\zmq\\backend\\cython\\checkrc.pxd\u001b[0m in \u001b[0;36mzmq.backend.cython.checkrc._check_rc\u001b[1;34m()\u001b[0m\n",
      "\u001b[1;31mKeyboardInterrupt\u001b[0m: "
     ]
    }
   ],
   "source": [
    "for i in dataset:\n",
    "    print(i[0],i[1])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "def transform(data, zy_list, wd_list, jd_list, sf_list,xl_list, columns):\n",
    "    # print(columns)\n",
    "    zy_index = columns.index('专业编码')\n",
    "    wd_index = columns.index('纬度')\n",
    "    jd_index = columns.index('经度')\n",
    "    sf_index = columns.index('省份编码')\n",
    "    xl_index = columns.index('学历编码')\n",
    "    result = []\n",
    "    for column in columns:\n",
    "        idx = columns.index(column)\n",
    "        if idx in [zy_index, wd_index, jd_index, sf_index,xl_index]:\n",
    "            if idx == zy_index:\n",
    "                t = [0] * len(zy_list)\n",
    "                t[zy_list.index(data[idx])] = 1\n",
    "                result.extend(t)\n",
    "            elif idx == wd_index:\n",
    "                t = [0] * len(wd_list)\n",
    "                t[wd_list.index(data[idx])] = 1\n",
    "                result.extend(t)\n",
    "            elif idx == jd_index:\n",
    "                t = [0] * len(jd_list)\n",
    "                t[jd_list.index(data[idx])] = 1\n",
    "                result.extend(t)\n",
    "            elif idx == sf_index:\n",
    "                t = [0] * len(sf_list)\n",
    "                t[sf_list.index(data[idx])] = 1\n",
    "                result.extend(t)\n",
    "            elif idx == xl_index:\n",
    "                t = [0] * len(xl_list)\n",
    "                t[xl_list.index(data[idx])] = 1\n",
    "                result.extend(t)\n",
    "        else:\n",
    "            result.append(data[idx])\n",
    "    return torch.tensor(result)\n",
    "class CustomDataset(Dataset):\n",
    "    def __init__(self, csv_path, transform=transform):\n",
    "        self.transform = transform  #数据预处理方法\n",
    "        df = pd.read_csv(csv_path, encoding='utf8') #读取数据\n",
    "        #纬度有nan值，采用前向填充\n",
    "        df = df.fillna(method=\"ffill\")\n",
    "        del df['专业']\n",
    "        del df['省份']\n",
    "        del df['城市']\n",
    "        #需要进行One-Hot编码的字段\n",
    "        self.zy =sorted(set(df[\"专业编码\"].values))\n",
    "        self.wd = sorted(set(df[\"纬度\"].values))\n",
    "        self.jd = sorted(set(df[\"经度\"].values))\n",
    "        self.sf = sorted(set(df[\"省份编码\"].values))\n",
    "        self.xl = sorted(set(df[\"学历编码\"].values))\n",
    "        \n",
    "        \n",
    "        self.df_label = df[\"薪酬\"]\n",
    "        del df[\"薪酬\"]\n",
    "        #对“综合能力”归一化处理\n",
    "        df[\"综合能力\"] = z_score(df[\"综合能力\"])\n",
    "        self.df_data = df \n",
    "        self.columns = self.df_data.columns.tolist()\n",
    "\n",
    "    def __getitem__(self, idx):  # 根据 idx 取出其中一个\n",
    "        data = self.df_data.iloc[idx].values\n",
    "        label = self.df_label.iloc[idx]\n",
    "        return transform(data,self.zy,self.wd,self.jd,self.sf,self.xl,self.columns),torch.tensor(label)\n",
    "    \n",
    "    def __len__(self):  # 总数据的多少\n",
    "        return df.count()[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "mean:37.07904970227501\n",
      "std:21.75875929994074\n"
     ]
    }
   ],
   "source": [
    "dataset = CustomDataset(\"./datas/salarys.csv\",transform=transform)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "255516"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dataset.__len__()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "tensor([ 0.0000,  1.0000,  0.0000,  0.0000,  0.0000,  0.0000,  0.0000,  0.0000,\n",
      "         0.0000,  0.0000,  0.0000,  0.0000,  0.0000,  0.0000,  0.0000,  0.0000,\n",
      "         0.0000,  0.0000,  0.0000,  0.0000,  0.0000,  0.0000,  0.0000,  0.0000,\n",
      "         0.0000,  0.0000,  0.0000,  0.0000,  0.0000,  0.0000,  0.0000,  0.0000,\n",
      "         0.0000,  0.0000,  0.0000,  0.0000,  0.0000,  0.0000,  0.0000,  0.0000,\n",
      "         0.0000,  0.0000,  0.0000,  0.0000,  0.0000,  0.0000,  0.0000,  0.0000,\n",
      "         0.0000,  0.0000,  0.0000,  0.0000,  0.0000,  0.0000,  0.0000,  0.0000,\n",
      "         0.0000,  0.0000,  0.0000,  0.0000,  0.0000,  0.0000,  0.0000,  0.0000,\n",
      "         0.0000,  0.0000,  0.0000,  0.0000,  0.0000,  0.0000,  0.0000,  0.0000,\n",
      "         0.0000,  0.0000,  0.0000,  0.0000,  0.0000,  0.0000,  0.0000,  0.0000,\n",
      "         0.0000,  0.0000,  0.0000,  0.0000,  0.0000,  0.0000,  0.0000,  0.0000,\n",
      "         0.0000,  0.0000,  0.0000,  0.0000,  0.0000,  0.0000,  0.0000,  0.0000,\n",
      "         0.0000,  0.0000,  0.0000,  0.0000,  0.0000,  0.0000,  0.0000,  0.0000,\n",
      "         0.0000,  0.0000,  0.0000,  0.0000,  0.0000,  0.0000,  0.0000,  0.0000,\n",
      "         0.0000,  0.0000,  0.0000,  0.0000,  0.0000,  0.0000,  0.0000,  0.0000,\n",
      "         0.0000,  0.0000,  0.0000,  0.0000,  0.0000,  0.0000,  0.0000,  0.0000,\n",
      "         0.0000,  0.0000,  0.0000,  0.0000,  0.0000,  0.0000,  0.0000,  0.0000,\n",
      "         0.0000,  0.0000,  0.0000,  0.0000,  0.0000,  0.0000,  0.0000,  0.0000,\n",
      "         0.0000,  0.0000,  0.0000,  0.0000,  0.0000,  0.0000,  0.0000,  0.0000,\n",
      "         0.0000,  0.0000,  0.0000,  0.0000,  0.0000,  0.0000,  0.0000,  0.0000,\n",
      "         0.0000,  0.0000,  0.0000,  0.0000,  0.0000,  0.0000,  0.0000,  0.0000,\n",
      "         0.0000,  0.0000,  0.0000,  0.0000,  0.0000,  0.0000,  0.0000,  0.0000,\n",
      "         0.0000,  0.0000,  0.0000,  0.0000,  0.0000,  0.0000,  0.0000,  0.0000,\n",
      "         0.0000,  0.0000,  0.0000,  0.0000,  0.0000,  0.0000,  0.0000,  0.0000,\n",
      "         0.0000,  0.0000,  0.0000,  0.0000,  0.0000,  0.0000,  0.0000,  0.0000,\n",
      "         0.0000,  0.0000,  0.0000,  0.0000,  0.0000,  1.0000,  0.0000,  0.0000,\n",
      "         0.0000,  0.0000,  0.0000,  0.0000,  0.0000,  0.0000,  0.0000,  0.0000,\n",
      "         0.0000,  0.0000,  0.0000,  0.0000,  0.0000,  0.0000,  0.0000,  0.0000,\n",
      "         0.0000,  0.0000,  0.0000,  0.0000,  0.0000,  0.0000,  1.0000,  0.0000,\n",
      "         0.0000,  0.0000,  0.0000,  0.0000,  0.0000,  0.0000,  0.0000,  0.0000,\n",
      "         0.0000,  0.0000,  0.0000,  0.0000,  0.0000,  0.0000,  0.0000,  0.0000,\n",
      "         0.0000,  0.0000,  0.0000,  0.0000,  0.0000,  0.0000,  0.0000,  0.0000,\n",
      "         0.0000,  0.0000,  0.0000,  0.0000,  0.0000,  0.0000,  0.0000,  0.0000,\n",
      "         0.0000,  0.0000,  0.0000,  0.0000,  0.0000,  0.0000,  0.0000,  0.0000,\n",
      "         0.0000,  0.0000,  0.0000,  0.0000,  0.0000,  0.0000,  1.0000,  0.0000,\n",
      "         0.0000,  0.0000,  0.0000,  0.0000,  0.0000,  0.0000,  0.0000,  1.0000,\n",
      "         0.0000,  0.0000,  0.0000,  0.0000,  0.0000,  0.0000,  0.0000,  0.0000,\n",
      "         0.0000,  0.0000,  0.0000,  0.0000,  0.0000,  0.0000,  0.0000,  0.0000,\n",
      "         0.0000,  0.0000,  0.0000,  0.0000,  0.0000,  0.0000,  0.0000,  0.0000,\n",
      "         0.0000,  0.0000,  0.0000,  0.0000,  0.0000,  1.0000,  0.0000,  0.0000,\n",
      "         0.0000,  0.0000,  0.0000,  0.0000,  0.0000,  0.0000, -0.7068])\n",
      "tensor(5531.9990)\n"
     ]
    }
   ],
   "source": [
    "for i in dataset:\n",
    "    data = i[0]\n",
    "    print(data)\n",
    "    print(i[1])\n",
    "    break"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "epoch: 0 , Train Loss: 66.858752 , Mean: -0.08 , Min: -0.90 , Max: 0.40 , Median: -0.08, Dealed/Records: 16384/255516,, Time: 2019.05.07 10:19:05\n",
      "epoch: 0 , Train Loss: 66.134241 , Mean: 0.32 , Min: -0.04 , Max: 0.89 , Median: 0.28, Dealed/Records: 32768/255516,, Time: 2019.05.07 10:19:12\n",
      "epoch: 0 , Train Loss: 66.591477 , Mean: 0.58 , Min: 0.18 , Max: 1.63 , Median: 0.53, Dealed/Records: 49152/255516,, Time: 2019.05.07 10:19:19\n",
      "epoch: 0 , Train Loss: 66.640330 , Mean: 0.95 , Min: 0.33 , Max: 2.53 , Median: 0.86, Dealed/Records: 65536/255516,, Time: 2019.05.07 10:19:26\n",
      "epoch: 0 , Train Loss: 66.948973 , Mean: 1.46 , Min: 0.60 , Max: 3.99 , Median: 1.33, Dealed/Records: 81920/255516,, Time: 2019.05.07 10:19:33\n",
      "epoch: 0 , Train Loss: 67.059333 , Mean: 2.14 , Min: 1.00 , Max: 6.31 , Median: 1.95, Dealed/Records: 98304/255516,, Time: 2019.05.07 10:19:39\n",
      "epoch: 0 , Train Loss: 66.325289 , Mean: 3.04 , Min: 1.43 , Max: 8.82 , Median: 2.79, Dealed/Records: 114688/255516,, Time: 2019.05.07 10:19:46\n",
      "epoch: 0 , Train Loss: 67.220272 , Mean: 4.19 , Min: 2.07 , Max: 12.19 , Median: 3.84, Dealed/Records: 131072/255516,, Time: 2019.05.07 10:19:53\n",
      "epoch: 0 , Train Loss: 66.263608 , Mean: 5.55 , Min: 2.93 , Max: 15.60 , Median: 5.12, Dealed/Records: 147456/255516,, Time: 2019.05.07 10:20:00\n",
      "epoch: 0 , Train Loss: 66.572586 , Mean: 7.27 , Min: 3.60 , Max: 21.33 , Median: 6.69, Dealed/Records: 163840/255516,, Time: 2019.05.07 10:20:07\n",
      "epoch: 0 , Train Loss: 66.714410 , Mean: 9.22 , Min: 4.76 , Max: 27.04 , Median: 8.53, Dealed/Records: 180224/255516,, Time: 2019.05.07 10:20:13\n",
      "epoch: 0 , Train Loss: 66.444941 , Mean: 11.65 , Min: 6.12 , Max: 33.05 , Median: 10.75, Dealed/Records: 196608/255516,, Time: 2019.05.07 10:20:20\n",
      "epoch: 0 , Train Loss: 66.406658 , Mean: 14.29 , Min: 7.55 , Max: 41.72 , Median: 13.25, Dealed/Records: 212992/255516,, Time: 2019.05.07 10:20:27\n",
      "epoch: 0 , Train Loss: 66.787801 , Mean: 17.50 , Min: 9.21 , Max: 50.35 , Median: 16.19, Dealed/Records: 229376/255516,, Time: 2019.05.07 10:20:34\n",
      "epoch: 0 , Train Loss: 66.343757 , Mean: 21.17 , Min: 11.48 , Max: 61.26 , Median: 19.64, Dealed/Records: 245760/255516,, Time: 2019.05.07 10:20:41\n",
      "epoch: 0 , Train Loss: 66.981760 , Mean: 25.23 , Min: 13.93 , Max: 72.44 , Median: 23.50, Dealed/Records: 262144/255516,, Time: 2019.05.07 10:20:45\n",
      "epoch: 1 , Train Loss: 66.633772 , Mean: 30.05 , Min: 15.06 , Max: 87.62 , Median: 27.86, Dealed/Records: 16384/255516,, Time: 2019.05.07 10:20:52\n",
      "epoch: 1 , Train Loss: 65.871687 , Mean: 35.42 , Min: 18.95 , Max: 103.18 , Median: 32.86, Dealed/Records: 32768/255516,, Time: 2019.05.07 10:20:58\n",
      "epoch: 1 , Train Loss: 66.285453 , Mean: 41.46 , Min: 22.52 , Max: 121.44 , Median: 38.34, Dealed/Records: 49152/255516,, Time: 2019.05.07 10:21:05\n",
      "epoch: 1 , Train Loss: 66.286786 , Mean: 48.31 , Min: 25.97 , Max: 135.95 , Median: 44.67, Dealed/Records: 65536/255516,, Time: 2019.05.07 10:21:12\n",
      "epoch: 1 , Train Loss: 66.541194 , Mean: 55.94 , Min: 30.05 , Max: 164.27 , Median: 51.65, Dealed/Records: 81920/255516,, Time: 2019.05.07 10:21:19\n",
      "epoch: 1 , Train Loss: 66.594241 , Mean: 64.24 , Min: 33.85 , Max: 190.01 , Median: 59.43, Dealed/Records: 98304/255516,, Time: 2019.05.07 10:21:25\n",
      "epoch: 1 , Train Loss: 65.799122 , Mean: 73.51 , Min: 39.12 , Max: 217.40 , Median: 68.11, Dealed/Records: 114688/255516,, Time: 2019.05.07 10:21:32\n",
      "epoch: 1 , Train Loss: 66.624304 , Mean: 84.08 , Min: 44.80 , Max: 248.48 , Median: 77.67, Dealed/Records: 131072/255516,, Time: 2019.05.07 10:21:39\n",
      "epoch: 1 , Train Loss: 65.595358 , Mean: 94.90 , Min: 50.77 , Max: 272.32 , Median: 88.01, Dealed/Records: 147456/255516,, Time: 2019.05.07 10:21:46\n",
      "epoch: 1 , Train Loss: 65.818687 , Mean: 108.02 , Min: 56.28 , Max: 321.07 , Median: 99.85, Dealed/Records: 163840/255516,, Time: 2019.05.07 10:21:52\n",
      "epoch: 1 , Train Loss: 65.880010 , Mean: 120.96 , Min: 63.58 , Max: 362.84 , Median: 112.17, Dealed/Records: 180224/255516,, Time: 2019.05.07 10:21:59\n",
      "epoch: 1 , Train Loss: 65.509102 , Mean: 136.82 , Min: 70.92 , Max: 401.55 , Median: 126.17, Dealed/Records: 196608/255516,, Time: 2019.05.07 10:22:06\n",
      "epoch: 1 , Train Loss: 65.377592 , Mean: 151.88 , Min: 78.09 , Max: 458.73 , Median: 140.80, Dealed/Records: 212992/255516,, Time: 2019.05.07 10:22:13\n",
      "epoch: 1 , Train Loss: 65.650006 , Mean: 169.99 , Min: 86.36 , Max: 509.92 , Median: 156.95, Dealed/Records: 229376/255516,, Time: 2019.05.07 10:22:19\n",
      "epoch: 1 , Train Loss: 65.087771 , Mean: 189.50 , Min: 99.39 , Max: 572.25 , Median: 175.37, Dealed/Records: 245760/255516,, Time: 2019.05.07 10:22:26\n",
      "epoch: 1 , Train Loss: 65.608275 , Mean: 209.44 , Min: 110.59 , Max: 630.57 , Median: 194.45, Dealed/Records: 262144/255516,, Time: 2019.05.07 10:22:30\n",
      "epoch: 2 , Train Loss: 65.119635 , Mean: 232.89 , Min: 115.47 , Max: 707.33 , Median: 215.13, Dealed/Records: 16384/255516,, Time: 2019.05.07 10:22:37\n",
      "epoch: 2 , Train Loss: 64.212424 , Mean: 257.41 , Min: 133.22 , Max: 781.39 , Median: 238.19, Dealed/Records: 32768/255516,, Time: 2019.05.07 10:22:44\n",
      "epoch: 2 , Train Loss: 64.471761 , Mean: 283.92 , Min: 148.09 , Max: 862.63 , Median: 261.93, Dealed/Records: 49152/255516,, Time: 2019.05.07 10:22:51\n",
      "epoch: 2 , Train Loss: 64.314687 , Mean: 312.84 , Min: 162.45 , Max: 917.32 , Median: 288.50, Dealed/Records: 65536/255516,, Time: 2019.05.07 10:22:57\n",
      "epoch: 2 , Train Loss: 64.389664 , Mean: 343.82 , Min: 176.73 , Max: 1046.67 , Median: 316.32, Dealed/Records: 81920/255516,, Time: 2019.05.07 10:23:04\n",
      "epoch: 2 , Train Loss: 64.263260 , Mean: 375.96 , Min: 193.79 , Max: 1149.65 , Median: 346.39, Dealed/Records: 98304/255516,, Time: 2019.05.07 10:23:11\n",
      "epoch: 2 , Train Loss: 63.287754 , Mean: 410.69 , Min: 211.19 , Max: 1258.48 , Median: 378.99, Dealed/Records: 114688/255516,, Time: 2019.05.07 10:23:18\n",
      "epoch: 2 , Train Loss: 63.905070 , Mean: 449.68 , Min: 231.61 , Max: 1375.52 , Median: 413.59, Dealed/Records: 131072/255516,, Time: 2019.05.07 10:23:24\n",
      "epoch: 2 , Train Loss: 62.674362 , Mean: 486.91 , Min: 252.28 , Max: 1446.96 , Median: 450.26, Dealed/Records: 147456/255516,, Time: 2019.05.07 10:23:31\n",
      "epoch: 2 , Train Loss: 62.652634 , Mean: 533.02 , Min: 271.99 , Max: 1634.30 , Median: 490.74, Dealed/Records: 163840/255516,, Time: 2019.05.07 10:23:38\n",
      "epoch: 2 , Train Loss: 62.508767 , Mean: 574.89 , Min: 294.74 , Max: 1776.59 , Median: 532.05, Dealed/Records: 180224/255516,, Time: 2019.05.07 10:23:45\n",
      "epoch: 2 , Train Loss: 61.862483 , Mean: 627.69 , Min: 318.59 , Max: 1896.36 , Median: 577.36, Dealed/Records: 196608/255516,, Time: 2019.05.07 10:23:51\n",
      "epoch: 2 , Train Loss: 61.504916 , Mean: 673.33 , Min: 340.59 , Max: 2090.00 , Median: 623.38, Dealed/Records: 212992/255516,, Time: 2019.05.07 10:23:58\n",
      "epoch: 2 , Train Loss: 61.508598 , Mean: 729.57 , Min: 365.60 , Max: 2246.23 , Median: 673.41, Dealed/Records: 229376/255516,, Time: 2019.05.07 10:24:05\n",
      "epoch: 2 , Train Loss: 60.658874 , Mean: 788.41 , Min: 402.00 , Max: 2439.12 , Median: 728.35, Dealed/Records: 245760/255516,, Time: 2019.05.07 10:24:12\n",
      "epoch: 2 , Train Loss: 60.911210 , Mean: 845.54 , Min: 436.84 , Max: 2609.15 , Median: 784.52, Dealed/Records: 262144/255516,, Time: 2019.05.07 10:24:16\n",
      "epoch: 3 , Train Loss: 60.091983 , Mean: 913.82 , Min: 451.61 , Max: 2836.82 , Median: 843.57, Dealed/Records: 16384/255516,, Time: 2019.05.07 10:24:22\n",
      "epoch: 3 , Train Loss: 58.857506 , Mean: 982.38 , Min: 500.50 , Max: 3047.75 , Median: 907.74, Dealed/Records: 32768/255516,, Time: 2019.05.07 10:24:29\n",
      "epoch: 3 , Train Loss: 58.776972 , Mean: 1055.06 , Min: 541.19 , Max: 3268.65 , Median: 972.60, Dealed/Records: 49152/255516,, Time: 2019.05.07 10:24:36\n",
      "epoch: 3 , Train Loss: 58.289259 , Mean: 1132.78 , Min: 578.77 , Max: 3391.40 , Median: 1043.51, Dealed/Records: 65536/255516,, Time: 2019.05.07 10:24:43\n",
      "epoch: 3 , Train Loss: 57.983312 , Mean: 1214.21 , Min: 614.47 , Max: 3765.46 , Median: 1115.89, Dealed/Records: 81920/255516,, Time: 2019.05.07 10:24:49\n",
      "epoch: 3 , Train Loss: 57.494926 , Mean: 1295.89 , Min: 659.47 , Max: 4031.03 , Median: 1192.77, Dealed/Records: 98304/255516,, Time: 2019.05.07 10:24:56\n",
      "epoch: 3 , Train Loss: 56.181004 , Mean: 1382.59 , Min: 701.04 , Max: 4308.32 , Median: 1274.38, Dealed/Records: 114688/255516,, Time: 2019.05.07 10:25:03\n"
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      "epoch: 3 , Train Loss: 56.395956 , Mean: 1479.76 , Min: 752.99 , Max: 4598.72 , Median: 1359.18, Dealed/Records: 131072/255516,, Time: 2019.05.07 10:25:10\n",
      "epoch: 3 , Train Loss: 54.794919 , Mean: 1566.87 , Min: 801.59 , Max: 4732.38 , Median: 1447.55, Dealed/Records: 147456/255516,, Time: 2019.05.07 10:25:16\n",
      "epoch: 3 , Train Loss: 54.313026 , Mean: 1678.71 , Min: 845.90 , Max: 5221.26 , Median: 1542.95, Dealed/Records: 163840/255516,, Time: 2019.05.07 10:25:23\n",
      "epoch: 3 , Train Loss: 53.833932 , Mean: 1772.62 , Min: 896.49 , Max: 5553.29 , Median: 1638.63, Dealed/Records: 180224/255516,, Time: 2019.05.07 10:25:30\n",
      "epoch: 3 , Train Loss: 52.697012 , Mean: 1896.32 , Min: 952.96 , Max: 5803.03 , Median: 1741.26, Dealed/Records: 196608/255516,, Time: 2019.05.07 10:25:37\n",
      "epoch: 3 , Train Loss: 51.982104 , Mean: 1993.52 , Min: 1000.53 , Max: 6263.37 , Median: 1844.12, Dealed/Records: 212992/255516,, Time: 2019.05.07 10:25:43\n",
      "epoch: 3 , Train Loss: 51.560118 , Mean: 2118.15 , Min: 1054.48 , Max: 6594.50 , Median: 1953.41, Dealed/Records: 229376/255516,, Time: 2019.05.07 10:25:50\n",
      "epoch: 3 , Train Loss: 50.255466 , Mean: 2245.57 , Min: 1129.81 , Max: 7019.79 , Median: 2071.96, Dealed/Records: 245760/255516,, Time: 2019.05.07 10:25:57\n",
      "epoch: 3 , Train Loss: 50.116074 , Mean: 2363.33 , Min: 1209.79 , Max: 7362.11 , Median: 2190.42, Dealed/Records: 262144/255516,, Time: 2019.05.07 10:26:01\n",
      "epoch: 4 , Train Loss: 48.803366 , Mean: 2507.81 , Min: 1235.16 , Max: 7850.72 , Median: 2312.38, Dealed/Records: 16384/255516,, Time: 2019.05.07 10:26:08\n",
      "epoch: 4 , Train Loss: 47.104013 , Mean: 2647.54 , Min: 1339.80 , Max: 8275.81 , Median: 2443.55, Dealed/Records: 32768/255516,, Time: 2019.05.07 10:26:14\n",
      "epoch: 4 , Train Loss: 46.554629 , Mean: 2793.32 , Min: 1421.37 , Max: 8706.01 , Median: 2572.69, Dealed/Records: 49152/255516,, Time: 2019.05.07 10:26:21\n",
      "epoch: 4 , Train Loss: 45.669317 , Mean: 2946.91 , Min: 1493.16 , Max: 8872.56 , Median: 2712.72, Dealed/Records: 65536/255516,, Time: 2019.05.07 10:26:28\n",
      "epoch: 4 , Train Loss: 44.862629 , Mean: 3104.57 , Min: 1560.73 , Max: 9666.49 , Median: 2851.39, Dealed/Records: 81920/255516,, Time: 2019.05.07 10:26:35\n",
      "epoch: 4 , Train Loss: 43.944740 , Mean: 3257.17 , Min: 1648.48 , Max: 10157.70 , Median: 2996.58, Dealed/Records: 98304/255516,, Time: 2019.05.07 10:26:42\n",
      "epoch: 4 , Train Loss: 42.336423 , Mean: 3416.63 , Min: 1721.16 , Max: 10660.08 , Median: 3147.32, Dealed/Records: 114688/255516,, Time: 2019.05.07 10:26:48\n",
      "epoch: 4 , Train Loss: 42.133603 , Mean: 3595.90 , Min: 1819.16 , Max: 11171.90 , Median: 3301.84, Dealed/Records: 131072/255516,, Time: 2019.05.07 10:26:55\n",
      "epoch: 4 , Train Loss: 40.181064 , Mean: 3744.49 , Min: 1905.88 , Max: 11289.44 , Median: 3459.44, Dealed/Records: 147456/255516,, Time: 2019.05.07 10:27:02\n",
      "epoch: 4 , Train Loss: 39.277720 , Mean: 3945.71 , Min: 1978.80 , Max: 12228.47 , Median: 3626.79, Dealed/Records: 163840/255516,, Time: 2019.05.07 10:27:09\n",
      "epoch: 4 , Train Loss: 38.613956 , Mean: 4097.88 , Min: 2060.14 , Max: 12767.33 , Median: 3788.95, Dealed/Records: 180224/255516,, Time: 2019.05.07 10:27:15\n",
      "epoch: 4 , Train Loss: 37.136334 , Mean: 4311.65 , Min: 2159.89 , Max: 13087.26 , Median: 3960.08, Dealed/Records: 196608/255516,, Time: 2019.05.07 10:27:22\n",
      "epoch: 4 , Train Loss: 36.229106 , Mean: 4458.09 , Min: 2230.09 , Max: 13865.65 , Median: 4125.91, Dealed/Records: 212992/255516,, Time: 2019.05.07 10:27:29\n",
      "epoch: 4 , Train Loss: 35.668547 , Mean: 4658.28 , Min: 2313.29 , Max: 14316.88 , Median: 4298.47, Dealed/Records: 229376/255516,, Time: 2019.05.07 10:27:36\n",
      "epoch: 4 , Train Loss: 34.213085 , Mean: 4856.07 , Min: 2433.64 , Max: 14948.40 , Median: 4485.61, Dealed/Records: 245760/255516,, Time: 2019.05.07 10:27:43\n",
      "epoch: 4 , Train Loss: 33.984684 , Mean: 5025.03 , Min: 2567.15 , Max: 15356.72 , Median: 4660.30, Dealed/Records: 262144/255516,, Time: 2019.05.07 10:27:47\n",
      "epoch: 5 , Train Loss: 32.674165 , Mean: 5240.99 , Min: 2578.91 , Max: 16050.41 , Median: 4837.76, Dealed/Records: 16384/255516,, Time: 2019.05.07 10:27:54\n",
      "epoch: 5 , Train Loss: 31.065964 , Mean: 5437.03 , Min: 2754.68 , Max: 16560.11 , Median: 5028.97, Dealed/Records: 32768/255516,, Time: 2019.05.07 10:28:01\n",
      "epoch: 5 , Train Loss: 30.586053 , Mean: 5634.96 , Min: 2865.94 , Max: 17030.59 , Median: 5198.32, Dealed/Records: 49152/255516,, Time: 2019.05.07 10:28:07\n",
      "epoch: 5 , Train Loss: 30.064334 , Mean: 5837.38 , Min: 2954.31 , Max: 16955.66 , Median: 5384.22, Dealed/Records: 65536/255516,, Time: 2019.05.07 10:28:14\n",
      "epoch: 5 , Train Loss: 29.407906 , Mean: 6035.69 , Min: 3047.42 , Max: 18057.88 , Median: 5557.14, Dealed/Records: 81920/255516,, Time: 2019.05.07 10:28:21\n",
      "epoch: 5 , Train Loss: 28.792625 , Mean: 6212.44 , Min: 3159.52 , Max: 18505.80 , Median: 5732.47, Dealed/Records: 98304/255516,, Time: 2019.05.07 10:28:28\n",
      "epoch: 5 , Train Loss: 28.018296 , Mean: 6389.37 , Min: 3222.47 , Max: 18925.04 , Median: 5904.90, Dealed/Records: 114688/255516,, Time: 2019.05.07 10:28:35\n",
      "epoch: 5 , Train Loss: 28.281917 , Mean: 6588.52 , Min: 3348.37 , Max: 19314.00 , Median: 6076.03, Dealed/Records: 131072/255516,, Time: 2019.05.07 10:28:41\n",
      "epoch: 5 , Train Loss: 26.938445 , Mean: 6720.44 , Min: 3439.53 , Max: 18941.74 , Median: 6233.00, Dealed/Records: 147456/255516,, Time: 2019.05.07 10:28:48\n",
      "epoch: 5 , Train Loss: 26.791435 , Mean: 6928.67 , Min: 3503.19 , Max: 19988.47 , Median: 6402.90, Dealed/Records: 163840/255516,, Time: 2019.05.07 10:28:55\n",
      "epoch: 5 , Train Loss: 26.826226 , Mean: 7039.71 , Min: 3566.29 , Max: 20267.46 , Median: 6542.79, Dealed/Records: 180224/255516,, Time: 2019.05.07 10:29:02\n",
      "epoch: 5 , Train Loss: 26.401167 , Mean: 7234.98 , Min: 3662.36 , Max: 20098.13 , Median: 6688.87, Dealed/Records: 196608/255516,, Time: 2019.05.07 10:29:09\n",
      "epoch: 5 , Train Loss: 26.071311 , Mean: 7311.16 , Min: 3676.80 , Max: 20714.19 , Median: 6804.33, Dealed/Records: 212992/255516,, Time: 2019.05.07 10:29:15\n",
      "epoch: 5 , Train Loss: 26.399865 , Mean: 7455.09 , Min: 3731.15 , Max: 20715.82 , Median: 6926.43, Dealed/Records: 229376/255516,, Time: 2019.05.07 10:29:22\n",
      "epoch: 5 , Train Loss: 25.955321 , Mean: 7579.93 , Min: 3865.68 , Max: 20987.88 , Median: 7055.50, Dealed/Records: 245760/255516,, Time: 2019.05.07 10:29:29\n",
      "epoch: 5 , Train Loss: 26.169059 , Mean: 7651.87 , Min: 3963.46 , Max: 20830.77 , Median: 7145.32, Dealed/Records: 262144/255516,, Time: 2019.05.07 10:29:33\n",
      "epoch: 6 , Train Loss: 25.945902 , Mean: 7771.33 , Min: 3853.73 , Max: 21157.15 , Median: 7231.35, Dealed/Records: 16384/255516,, Time: 2019.05.07 10:29:40\n",
      "epoch: 6 , Train Loss: 25.407607 , Mean: 7851.92 , Min: 4066.11 , Max: 21129.88 , Median: 7327.91, Dealed/Records: 32768/255516,, Time: 2019.05.07 10:29:47\n",
      "epoch: 6 , Train Loss: 25.479541 , Mean: 7922.12 , Min: 4108.07 , Max: 21015.45 , Median: 7372.29, Dealed/Records: 49152/255516,, Time: 2019.05.07 10:29:53\n",
      "epoch: 6 , Train Loss: 25.713609 , Mean: 7988.36 , Min: 4102.10 , Max: 20253.17 , Median: 7446.54, Dealed/Records: 65536/255516,, Time: 2019.05.07 10:30:00\n",
      "epoch: 6 , Train Loss: 25.454103 , Mean: 8040.11 , Min: 4204.16 , Max: 21006.42 , Median: 7482.27, Dealed/Records: 81920/255516,, Time: 2019.05.07 10:30:07\n",
      "epoch: 6 , Train Loss: 25.269949 , Mean: 8058.03 , Min: 4198.29 , Max: 20868.30 , Median: 7521.89, Dealed/Records: 98304/255516,, Time: 2019.05.07 10:30:14\n",
      "epoch: 6 , Train Loss: 25.157893 , Mean: 8069.32 , Min: 4135.16 , Max: 20708.56 , Median: 7556.33, Dealed/Records: 114688/255516,, Time: 2019.05.07 10:30:21\n",
      "epoch: 6 , Train Loss: 25.578170 , Mean: 8101.24 , Min: 4229.76 , Max: 20572.65 , Median: 7567.16, Dealed/Records: 131072/255516,, Time: 2019.05.07 10:30:28\n",
      "epoch: 6 , Train Loss: 24.548244 , Mean: 8060.74 , Min: 4239.57 , Max: 19505.95 , Median: 7568.81, Dealed/Records: 147456/255516,, Time: 2019.05.07 10:30:34\n",
      "epoch: 6 , Train Loss: 24.610037 , Mean: 8100.07 , Min: 4142.21 , Max: 20152.58 , Median: 7601.50, Dealed/Records: 163840/255516,, Time: 2019.05.07 10:30:41\n",
      "epoch: 6 , Train Loss: 24.636787 , Mean: 8041.15 , Min: 4189.96 , Max: 19927.07 , Median: 7555.89, Dealed/Records: 180224/255516,, Time: 2019.05.07 10:30:48\n",
      "epoch: 6 , Train Loss: 24.290641 , Mean: 8066.72 , Min: 4219.24 , Max: 19123.50 , Median: 7575.35, Dealed/Records: 196608/255516,, Time: 2019.05.07 10:30:55\n"
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      "epoch: 6 , Train Loss: 23.976928 , Mean: 7987.18 , Min: 4083.58 , Max: 19450.15 , Median: 7518.73, Dealed/Records: 212992/255516,, Time: 2019.05.07 10:31:03\n",
      "epoch: 6 , Train Loss: 24.210124 , Mean: 7977.20 , Min: 4071.43 , Max: 19010.39 , Median: 7503.04, Dealed/Records: 229376/255516,, Time: 2019.05.07 10:31:10\n",
      "epoch: 6 , Train Loss: 23.792802 , Mean: 7953.49 , Min: 4231.27 , Max: 18971.10 , Median: 7490.19, Dealed/Records: 245760/255516,, Time: 2019.05.07 10:31:17\n",
      "epoch: 6 , Train Loss: 23.927666 , Mean: 7900.10 , Min: 4222.77 , Max: 18362.18 , Median: 7470.77, Dealed/Records: 262144/255516,, Time: 2019.05.07 10:31:21\n",
      "epoch: 7 , Train Loss: 23.556953 , Mean: 7886.17 , Min: 3948.83 , Max: 18525.22 , Median: 7425.17, Dealed/Records: 16384/255516,, Time: 2019.05.07 10:31:29\n",
      "epoch: 7 , Train Loss: 22.948075 , Mean: 7851.43 , Min: 4205.07 , Max: 18210.33 , Median: 7424.59, Dealed/Records: 32768/255516,, Time: 2019.05.07 10:31:36\n",
      "epoch: 7 , Train Loss: 22.967807 , Mean: 7819.20 , Min: 4195.49 , Max: 17810.26 , Median: 7357.12, Dealed/Records: 49152/255516,, Time: 2019.05.07 10:31:45\n",
      "epoch: 7 , Train Loss: 23.116753 , Mean: 7795.74 , Min: 4088.91 , Max: 17061.66 , Median: 7355.05, Dealed/Records: 65536/255516,, Time: 2019.05.07 10:31:56\n",
      "epoch: 7 , Train Loss: 22.837617 , Mean: 7775.72 , Min: 4219.26 , Max: 17619.42 , Median: 7322.97, Dealed/Records: 81920/255516,, Time: 2019.05.07 10:32:06\n",
      "epoch: 7 , Train Loss: 22.764046 , Mean: 7733.17 , Min: 4168.53 , Max: 17363.73 , Median: 7299.53, Dealed/Records: 98304/255516,, Time: 2019.05.07 10:32:16\n",
      "epoch: 7 , Train Loss: 22.480904 , Mean: 7694.60 , Min: 4022.32 , Max: 17135.62 , Median: 7294.89, Dealed/Records: 114688/255516,, Time: 2019.05.07 10:32:37\n",
      "epoch: 7 , Train Loss: 23.038476 , Mean: 7685.06 , Min: 4148.70 , Max: 17017.63 , Median: 7267.35, Dealed/Records: 131072/255516,, Time: 2019.05.07 10:32:49\n",
      "epoch: 7 , Train Loss: 21.991104 , Mean: 7626.94 , Min: 4143.04 , Max: 16058.44 , Median: 7230.81, Dealed/Records: 147456/255516,, Time: 2019.05.07 10:32:56\n",
      "epoch: 7 , Train Loss: 22.088389 , Mean: 7643.08 , Min: 3937.23 , Max: 16608.26 , Median: 7251.44, Dealed/Records: 163840/255516,, Time: 2019.05.07 10:33:06\n",
      "epoch: 7 , Train Loss: 22.289892 , Mean: 7587.62 , Min: 4047.76 , Max: 16435.05 , Median: 7192.81, Dealed/Records: 180224/255516,, Time: 2019.05.07 10:33:15\n",
      "epoch: 7 , Train Loss: 21.815781 , Mean: 7605.98 , Min: 4113.05 , Max: 15596.62 , Median: 7224.83, Dealed/Records: 196608/255516,, Time: 2019.05.07 10:33:21\n",
      "epoch: 7 , Train Loss: 21.774569 , Mean: 7550.71 , Min: 3920.07 , Max: 16134.75 , Median: 7175.47, Dealed/Records: 212992/255516,, Time: 2019.05.07 10:33:28\n",
      "epoch: 7 , Train Loss: 22.069440 , Mean: 7556.18 , Min: 3928.09 , Max: 15779.73 , Median: 7193.28, Dealed/Records: 229376/255516,, Time: 2019.05.07 10:33:35\n",
      "epoch: 7 , Train Loss: 21.709412 , Mean: 7551.29 , Min: 4146.76 , Max: 15935.83 , Median: 7192.05, Dealed/Records: 245760/255516,, Time: 2019.05.07 10:33:42\n",
      "epoch: 7 , Train Loss: 22.046512 , Mean: 7537.60 , Min: 4151.10 , Max: 15403.85 , Median: 7189.74, Dealed/Records: 262144/255516,, Time: 2019.05.07 10:33:46\n",
      "epoch: 8 , Train Loss: 21.621508 , Mean: 7547.10 , Min: 3799.00 , Max: 15770.45 , Median: 7183.40, Dealed/Records: 16384/255516,, Time: 2019.05.07 10:33:53\n",
      "epoch: 8 , Train Loss: 21.017264 , Mean: 7544.34 , Min: 4164.60 , Max: 15629.59 , Median: 7208.79, Dealed/Records: 32768/255516,, Time: 2019.05.07 10:34:00\n",
      "epoch: 8 , Train Loss: 21.150434 , Mean: 7548.23 , Min: 4008.33 , Max: 15237.34 , Median: 7169.68, Dealed/Records: 49152/255516,, Time: 2019.05.07 10:34:07\n",
      "epoch: 8 , Train Loss: 21.316708 , Mean: 7561.45 , Min: 4032.16 , Max: 14836.32 , Median: 7213.04, Dealed/Records: 65536/255516,, Time: 2019.05.07 10:34:14\n",
      "epoch: 8 , Train Loss: 21.108786 , Mean: 7584.65 , Min: 4187.65 , Max: 15454.55 , Median: 7231.40, Dealed/Records: 81920/255516,, Time: 2019.05.07 10:34:20\n",
      "epoch: 8 , Train Loss: 21.149576 , Mean: 7581.62 , Min: 4102.06 , Max: 15355.44 , Median: 7231.15, Dealed/Records: 98304/255516,, Time: 2019.05.07 10:34:27\n",
      "epoch: 8 , Train Loss: 20.788833 , Mean: 7581.01 , Min: 4027.06 , Max: 15222.62 , Median: 7259.09, Dealed/Records: 114688/255516,, Time: 2019.05.07 10:34:34\n",
      "epoch: 8 , Train Loss: 21.416402 , Mean: 7607.49 , Min: 4091.06 , Max: 15291.10 , Median: 7278.46, Dealed/Records: 131072/255516,, Time: 2019.05.07 10:34:41\n",
      "epoch: 8 , Train Loss: 20.365598 , Mean: 7589.58 , Min: 4091.54 , Max: 14554.95 , Median: 7258.23, Dealed/Records: 147456/255516,, Time: 2019.05.07 10:34:48\n",
      "epoch: 8 , Train Loss: 20.492059 , Mean: 7635.83 , Min: 3954.14 , Max: 15162.63 , Median: 7318.73, Dealed/Records: 163840/255516,, Time: 2019.05.07 10:34:55\n",
      "epoch: 8 , Train Loss: 20.720983 , Mean: 7616.76 , Min: 3988.99 , Max: 15053.07 , Median: 7271.52, Dealed/Records: 180224/255516,, Time: 2019.05.07 10:35:02\n",
      "epoch: 8 , Train Loss: 20.190715 , Mean: 7659.73 , Min: 4162.39 , Max: 14556.64 , Median: 7338.04, Dealed/Records: 196608/255516,, Time: 2019.05.07 10:35:09\n",
      "epoch: 8 , Train Loss: 20.233186 , Mean: 7637.88 , Min: 4005.04 , Max: 14981.94 , Median: 7315.60, Dealed/Records: 212992/255516,, Time: 2019.05.07 10:35:15\n",
      "epoch: 8 , Train Loss: 20.508607 , Mean: 7666.80 , Min: 4007.54 , Max: 14675.43 , Median: 7344.78, Dealed/Records: 229376/255516,, Time: 2019.05.07 10:35:22\n",
      "epoch: 8 , Train Loss: 20.196559 , Mean: 7679.39 , Min: 4101.41 , Max: 15026.26 , Median: 7370.23, Dealed/Records: 245760/255516,, Time: 2019.05.07 10:35:29\n",
      "epoch: 8 , Train Loss: 20.526581 , Mean: 7691.27 , Min: 4052.24 , Max: 14509.99 , Median: 7371.89, Dealed/Records: 262144/255516,, Time: 2019.05.07 10:35:33\n",
      "epoch: 9 , Train Loss: 20.104024 , Mean: 7710.75 , Min: 3884.41 , Max: 15027.22 , Median: 7389.38, Dealed/Records: 16384/255516,, Time: 2019.05.07 10:35:40\n",
      "epoch: 9 , Train Loss: 19.560065 , Mean: 7716.76 , Min: 4109.48 , Max: 14972.53 , Median: 7413.03, Dealed/Records: 32768/255516,, Time: 2019.05.07 10:35:47\n",
      "epoch: 9 , Train Loss: 19.693085 , Mean: 7729.38 , Min: 3872.05 , Max: 14514.18 , Median: 7379.92, Dealed/Records: 49152/255516,, Time: 2019.05.07 10:35:54\n",
      "epoch: 9 , Train Loss: 19.867584 , Mean: 7747.55 , Min: 4142.15 , Max: 14580.79 , Median: 7421.33, Dealed/Records: 65536/255516,, Time: 2019.05.07 10:36:00\n",
      "epoch: 9 , Train Loss: 19.668764 , Mean: 7778.77 , Min: 4115.47 , Max: 14925.03 , Median: 7452.78, Dealed/Records: 81920/255516,, Time: 2019.05.07 10:36:07\n",
      "epoch: 9 , Train Loss: 19.762802 , Mean: 7775.46 , Min: 3997.27 , Max: 14889.46 , Median: 7435.86, Dealed/Records: 98304/255516,, Time: 2019.05.07 10:36:14\n",
      "epoch: 9 , Train Loss: 19.411409 , Mean: 7772.01 , Min: 4155.33 , Max: 14718.18 , Median: 7481.44, Dealed/Records: 114688/255516,, Time: 2019.05.07 10:36:21\n",
      "epoch: 9 , Train Loss: 20.028511 , Mean: 7794.86 , Min: 4005.44 , Max: 14865.51 , Median: 7481.53, Dealed/Records: 131072/255516,, Time: 2019.05.07 10:36:28\n",
      "epoch: 9 , Train Loss: 19.013205 , Mean: 7772.43 , Min: 4023.77 , Max: 14286.06 , Median: 7451.76, Dealed/Records: 147456/255516,, Time: 2019.05.07 10:36:35\n",
      "epoch: 9 , Train Loss: 19.171884 , Mean: 7809.02 , Min: 4013.44 , Max: 14806.06 , Median: 7505.98, Dealed/Records: 163840/255516,, Time: 2019.05.07 10:36:42\n",
      "epoch: 9 , Train Loss: 19.399621 , Mean: 7783.02 , Min: 3845.56 , Max: 14631.21 , Median: 7437.83, Dealed/Records: 180224/255516,, Time: 2019.05.07 10:36:49\n",
      "epoch: 9 , Train Loss: 18.852625 , Mean: 7813.31 , Min: 4040.01 , Max: 14385.32 , Median: 7504.90, Dealed/Records: 196608/255516,, Time: 2019.05.07 10:36:55\n",
      "epoch: 9 , Train Loss: 18.952991 , Mean: 7784.19 , Min: 3840.54 , Max: 14600.14 , Median: 7472.77, Dealed/Records: 212992/255516,, Time: 2019.05.07 10:37:02\n",
      "epoch: 9 , Train Loss: 19.214592 , Mean: 7801.10 , Min: 3853.38 , Max: 14291.24 , Median: 7486.07, Dealed/Records: 229376/255516,, Time: 2019.05.07 10:37:09\n",
      "epoch: 9 , Train Loss: 18.952823 , Mean: 7797.87 , Min: 3949.86 , Max: 14707.22 , Median: 7486.96, Dealed/Records: 245760/255516,, Time: 2019.05.07 10:37:16\n",
      "epoch: 9 , Train Loss: 19.267610 , Mean: 7803.18 , Min: 3903.14 , Max: 14326.12 , Median: 7477.78, Dealed/Records: 262144/255516,, Time: 2019.05.07 10:37:20\n",
      "epoch: 10 , Train Loss: 18.869080 , Mean: 7806.19 , Min: 3867.02 , Max: 14721.50 , Median: 7485.64, Dealed/Records: 16384/255516,, Time: 2019.05.07 10:37:27\n"
     ]
    },
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     "output_type": "stream",
     "text": [
      "epoch: 10 , Train Loss: 18.372205 , Mean: 7795.64 , Min: 3849.49 , Max: 14689.28 , Median: 7479.61, Dealed/Records: 32768/255516,, Time: 2019.05.07 10:37:34\n",
      "epoch: 10 , Train Loss: 18.504512 , Mean: 7795.89 , Min: 3659.52 , Max: 14147.50 , Median: 7441.42, Dealed/Records: 49152/255516,, Time: 2019.05.07 10:37:41\n",
      "epoch: 10 , Train Loss: 18.684013 , Mean: 7800.55 , Min: 3966.65 , Max: 14425.20 , Median: 7469.31, Dealed/Records: 65536/255516,, Time: 2019.05.07 10:37:48\n",
      "epoch: 10 , Train Loss: 18.501105 , Mean: 7825.04 , Min: 3932.56 , Max: 14613.25 , Median: 7480.61, Dealed/Records: 81920/255516,, Time: 2019.05.07 10:37:55\n",
      "epoch: 10 , Train Loss: 18.635661 , Mean: 7809.10 , Min: 3789.24 , Max: 14618.53 , Median: 7460.86, Dealed/Records: 98304/255516,, Time: 2019.05.07 10:38:02\n",
      "epoch: 10 , Train Loss: 18.276185 , Mean: 7794.09 , Min: 3984.25 , Max: 14398.35 , Median: 7486.17, Dealed/Records: 114688/255516,, Time: 2019.05.07 10:38:08\n",
      "epoch: 10 , Train Loss: 18.895426 , Mean: 7808.26 , Min: 3804.74 , Max: 14571.55 , Median: 7480.23, Dealed/Records: 131072/255516,, Time: 2019.05.07 10:38:15\n",
      "epoch: 10 , Train Loss: 17.892542 , Mean: 7777.87 , Min: 3838.68 , Max: 14279.56 , Median: 7436.57, Dealed/Records: 147456/255516,, Time: 2019.05.07 10:38:22\n",
      "epoch: 10 , Train Loss: 18.076259 , Mean: 7804.67 , Min: 3805.51 , Max: 14568.12 , Median: 7495.81, Dealed/Records: 163840/255516,, Time: 2019.05.07 10:38:29\n",
      "epoch: 10 , Train Loss: 18.310417 , Mean: 7773.88 , Min: 3602.80 , Max: 14304.85 , Median: 7411.18, Dealed/Records: 180224/255516,, Time: 2019.05.07 10:38:36\n",
      "epoch: 10 , Train Loss: 17.731245 , Mean: 7796.80 , Min: 3790.25 , Max: 14184.41 , Median: 7477.05, Dealed/Records: 196608/255516,, Time: 2019.05.07 10:38:44\n",
      "epoch: 10 , Train Loss: 17.884864 , Mean: 7766.30 , Min: 3578.56 , Max: 14329.29 , Median: 7448.36, Dealed/Records: 212992/255516,, Time: 2019.05.07 10:38:52\n",
      "epoch: 10 , Train Loss: 18.140511 , Mean: 7779.46 , Min: 3608.21 , Max: 14229.06 , Median: 7447.65, Dealed/Records: 229376/255516,, Time: 2019.05.07 10:39:01\n",
      "epoch: 10 , Train Loss: 17.905635 , Mean: 7770.38 , Min: 3713.93 , Max: 14513.27 , Median: 7444.21, Dealed/Records: 245760/255516,, Time: 2019.05.07 10:39:09\n",
      "epoch: 10 , Train Loss: 18.219562 , Mean: 7779.21 , Min: 3679.67 , Max: 14205.88 , Median: 7421.87, Dealed/Records: 262144/255516,, Time: 2019.05.07 10:39:15\n",
      "epoch: 11 , Train Loss: 17.843483 , Mean: 7778.66 , Min: 3644.17 , Max: 14568.59 , Median: 7434.78, Dealed/Records: 16384/255516,, Time: 2019.05.07 10:39:22\n",
      "epoch: 11 , Train Loss: 17.369288 , Mean: 7763.82 , Min: 3558.92 , Max: 14581.21 , Median: 7430.49, Dealed/Records: 32768/255516,, Time: 2019.05.07 10:39:29\n",
      "epoch: 11 , Train Loss: 17.508372 , Mean: 7765.10 , Min: 3409.44 , Max: 14171.23 , Median: 7387.06, Dealed/Records: 49152/255516,, Time: 2019.05.07 10:39:36\n",
      "epoch: 11 , Train Loss: 17.694609 , Mean: 7769.38 , Min: 3694.86 , Max: 14371.26 , Median: 7415.83, Dealed/Records: 65536/255516,, Time: 2019.05.07 10:39:44\n",
      "epoch: 11 , Train Loss: 17.529427 , Mean: 7800.30 , Min: 3716.30 , Max: 14524.73 , Median: 7448.26, Dealed/Records: 81920/255516,, Time: 2019.05.07 10:39:52\n",
      "epoch: 11 , Train Loss: 17.694273 , Mean: 7784.30 , Min: 3568.29 , Max: 14596.85 , Median: 7407.07, Dealed/Records: 98304/255516,, Time: 2019.05.07 10:40:00\n",
      "epoch: 11 , Train Loss: 17.331585 , Mean: 7769.96 , Min: 3790.42 , Max: 14350.37 , Median: 7438.42, Dealed/Records: 114688/255516,, Time: 2019.05.07 10:40:07\n",
      "epoch: 11 , Train Loss: 17.953053 , Mean: 7787.72 , Min: 3597.50 , Max: 14548.39 , Median: 7429.97, Dealed/Records: 131072/255516,, Time: 2019.05.07 10:40:14\n",
      "epoch: 11 , Train Loss: 16.962368 , Mean: 7759.37 , Min: 3646.73 , Max: 14413.08 , Median: 7391.08, Dealed/Records: 147456/255516,, Time: 2019.05.07 10:40:23\n",
      "epoch: 11 , Train Loss: 17.170634 , Mean: 7787.28 , Min: 3607.42 , Max: 14643.07 , Median: 7451.85, Dealed/Records: 163840/255516,, Time: 2019.05.07 10:40:35\n",
      "epoch: 11 , Train Loss: 17.406431 , Mean: 7760.00 , Min: 3379.56 , Max: 14515.42 , Median: 7374.17, Dealed/Records: 180224/255516,, Time: 2019.05.07 10:40:44\n",
      "epoch: 11 , Train Loss: 16.806874 , Mean: 7784.74 , Min: 3559.22 , Max: 14261.36 , Median: 7447.32, Dealed/Records: 196608/255516,, Time: 2019.05.07 10:40:51\n",
      "epoch: 11 , Train Loss: 17.000372 , Mean: 7758.41 , Min: 3344.62 , Max: 14552.86 , Median: 7406.10, Dealed/Records: 212992/255516,, Time: 2019.05.07 10:40:58\n",
      "epoch: 11 , Train Loss: 17.251103 , Mean: 7774.07 , Min: 3392.53 , Max: 14545.74 , Median: 7423.32, Dealed/Records: 229376/255516,, Time: 2019.05.07 10:41:05\n",
      "epoch: 11 , Train Loss: 17.042507 , Mean: 7764.36 , Min: 3509.69 , Max: 14675.92 , Median: 7406.70, Dealed/Records: 245760/255516,, Time: 2019.05.07 10:41:12\n",
      "epoch: 11 , Train Loss: 17.342709 , Mean: 7779.26 , Min: 3494.39 , Max: 14447.53 , Median: 7396.15, Dealed/Records: 262144/255516,, Time: 2019.05.07 10:41:16\n",
      "epoch: 12 , Train Loss: 16.998560 , Mean: 7778.96 , Min: 3460.10 , Max: 14777.17 , Median: 7414.31, Dealed/Records: 16384/255516,, Time: 2019.05.07 10:41:23\n",
      "epoch: 12 , Train Loss: 16.553638 , Mean: 7761.44 , Min: 3330.72 , Max: 14825.21 , Median: 7412.01, Dealed/Records: 32768/255516,, Time: 2019.05.07 10:41:30\n",
      "epoch: 12 , Train Loss: 16.686770 , Mean: 7764.91 , Min: 3207.39 , Max: 14477.92 , Median: 7351.39, Dealed/Records: 49152/255516,, Time: 2019.05.07 10:41:36\n",
      "epoch: 12 , Train Loss: 16.884362 , Mean: 7768.86 , Min: 3491.68 , Max: 14587.34 , Median: 7385.23, Dealed/Records: 65536/255516,, Time: 2019.05.07 10:41:48\n",
      "epoch: 12 , Train Loss: 16.730404 , Mean: 7805.25 , Min: 3547.68 , Max: 14775.69 , Median: 7433.94, Dealed/Records: 81920/255516,, Time: 2019.05.07 10:41:55\n",
      "epoch: 12 , Train Loss: 16.913516 , Mean: 7787.59 , Min: 3394.26 , Max: 14916.03 , Median: 7380.42, Dealed/Records: 98304/255516,, Time: 2019.05.07 10:42:02\n",
      "epoch: 12 , Train Loss: 16.564613 , Mean: 7771.58 , Min: 3625.56 , Max: 14613.46 , Median: 7409.43, Dealed/Records: 114688/255516,, Time: 2019.05.07 10:42:10\n",
      "epoch: 12 , Train Loss: 17.177518 , Mean: 7790.71 , Min: 3429.11 , Max: 14834.65 , Median: 7403.55, Dealed/Records: 131072/255516,, Time: 2019.05.07 10:42:16\n",
      "epoch: 12 , Train Loss: 16.206463 , Mean: 7760.58 , Min: 3491.10 , Max: 14647.30 , Median: 7364.80, Dealed/Records: 147456/255516,, Time: 2019.05.07 10:42:23\n",
      "epoch: 12 , Train Loss: 16.436813 , Mean: 7787.19 , Min: 3450.81 , Max: 14993.51 , Median: 7428.62, Dealed/Records: 163840/255516,, Time: 2019.05.07 10:42:30\n",
      "epoch: 12 , Train Loss: 16.667262 , Mean: 7759.20 , Min: 3201.26 , Max: 14971.96 , Median: 7334.40, Dealed/Records: 180224/255516,, Time: 2019.05.07 10:42:37\n",
      "epoch: 12 , Train Loss: 16.059965 , Mean: 7782.98 , Min: 3368.80 , Max: 14531.98 , Median: 7405.53, Dealed/Records: 196608/255516,, Time: 2019.05.07 10:42:44\n",
      "epoch: 12 , Train Loss: 16.282082 , Mean: 7756.10 , Min: 3151.39 , Max: 15002.48 , Median: 7379.84, Dealed/Records: 212992/255516,, Time: 2019.05.07 10:42:51\n",
      "epoch: 12 , Train Loss: 16.529705 , Mean: 7770.87 , Min: 3207.11 , Max: 15015.77 , Median: 7385.10, Dealed/Records: 229376/255516,, Time: 2019.05.07 10:42:58\n",
      "epoch: 12 , Train Loss: 16.345197 , Mean: 7757.45 , Min: 3339.72 , Max: 14973.61 , Median: 7371.08, Dealed/Records: 245760/255516,, Time: 2019.05.07 10:43:05\n",
      "epoch: 12 , Train Loss: 16.630783 , Mean: 7774.20 , Min: 3342.92 , Max: 14869.48 , Median: 7347.01, Dealed/Records: 262144/255516,, Time: 2019.05.07 10:43:09\n",
      "epoch: 13 , Train Loss: 16.319136 , Mean: 7771.89 , Min: 3301.15 , Max: 15074.80 , Median: 7390.66, Dealed/Records: 16384/255516,, Time: 2019.05.07 10:43:16\n",
      "epoch: 13 , Train Loss: 15.901420 , Mean: 7749.01 , Min: 3145.36 , Max: 15164.30 , Median: 7372.63, Dealed/Records: 32768/255516,, Time: 2019.05.07 10:43:23\n",
      "epoch: 13 , Train Loss: 16.025629 , Mean: 7752.39 , Min: 3042.01 , Max: 14810.13 , Median: 7307.76, Dealed/Records: 49152/255516,, Time: 2019.05.07 10:43:29\n",
      "epoch: 13 , Train Loss: 16.235738 , Mean: 7754.11 , Min: 3284.47 , Max: 14844.37 , Median: 7336.59, Dealed/Records: 65536/255516,, Time: 2019.05.07 10:43:36\n",
      "epoch: 13 , Train Loss: 16.092684 , Mean: 7793.84 , Min: 3387.24 , Max: 15056.55 , Median: 7391.90, Dealed/Records: 81920/255516,, Time: 2019.05.07 10:43:43\n"
     ]
    },
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     "output_type": "stream",
     "text": [
      "epoch: 13 , Train Loss: 16.289164 , Mean: 7773.48 , Min: 3253.76 , Max: 15253.30 , Median: 7342.14, Dealed/Records: 98304/255516,, Time: 2019.05.07 10:43:50\n",
      "epoch: 13 , Train Loss: 15.953169 , Mean: 7754.81 , Min: 3410.87 , Max: 14877.44 , Median: 7359.44, Dealed/Records: 114688/255516,, Time: 2019.05.07 10:43:57\n",
      "epoch: 13 , Train Loss: 16.560201 , Mean: 7774.64 , Min: 3284.42 , Max: 15102.79 , Median: 7357.49, Dealed/Records: 131072/255516,, Time: 2019.05.07 10:44:04\n",
      "epoch: 13 , Train Loss: 15.606158 , Mean: 7742.25 , Min: 3358.04 , Max: 14896.74 , Median: 7317.16, Dealed/Records: 147456/255516,, Time: 2019.05.07 10:44:11\n",
      "epoch: 13 , Train Loss: 15.855525 , Mean: 7768.26 , Min: 3321.39 , Max: 15314.67 , Median: 7370.63, Dealed/Records: 163840/255516,, Time: 2019.05.07 10:44:18\n",
      "epoch: 13 , Train Loss: 16.079089 , Mean: 7739.80 , Min: 3062.21 , Max: 15375.82 , Median: 7288.20, Dealed/Records: 180224/255516,, Time: 2019.05.07 10:44:24\n",
      "epoch: 13 , Train Loss: 15.470611 , Mean: 7763.64 , Min: 3197.63 , Max: 14865.18 , Median: 7353.01, Dealed/Records: 196608/255516,, Time: 2019.05.07 10:44:31\n",
      "epoch: 13 , Train Loss: 15.713988 , Mean: 7736.74 , Min: 2998.36 , Max: 15385.91 , Median: 7339.57, Dealed/Records: 212992/255516,, Time: 2019.05.07 10:44:38\n",
      "epoch: 13 , Train Loss: 15.961332 , Mean: 7751.87 , Min: 3049.34 , Max: 15424.26 , Median: 7331.72, Dealed/Records: 229376/255516,, Time: 2019.05.07 10:44:46\n",
      "epoch: 13 , Train Loss: 15.795380 , Mean: 7736.41 , Min: 3198.43 , Max: 15203.84 , Median: 7318.37, Dealed/Records: 245760/255516,, Time: 2019.05.07 10:44:52\n",
      "epoch: 13 , Train Loss: 16.071116 , Mean: 7755.75 , Min: 3224.86 , Max: 15226.46 , Median: 7296.53, Dealed/Records: 262144/255516,, Time: 2019.05.07 10:44:57\n",
      "epoch: 14 , Train Loss: 15.785453 , Mean: 7753.39 , Min: 3170.90 , Max: 15302.38 , Median: 7355.69, Dealed/Records: 16384/255516,, Time: 2019.05.07 10:45:04\n",
      "epoch: 14 , Train Loss: 15.391205 , Mean: 7727.00 , Min: 3002.45 , Max: 15445.34 , Median: 7327.13, Dealed/Records: 32768/255516,, Time: 2019.05.07 10:45:10\n",
      "epoch: 14 , Train Loss: 15.506058 , Mean: 7731.92 , Min: 2920.93 , Max: 15096.25 , Median: 7253.58, Dealed/Records: 49152/255516,, Time: 2019.05.07 10:45:17\n",
      "epoch: 14 , Train Loss: 15.727916 , Mean: 7733.12 , Min: 3130.70 , Max: 15133.96 , Median: 7282.37, Dealed/Records: 65536/255516,, Time: 2019.05.07 10:45:24\n",
      "epoch: 14 , Train Loss: 15.595391 , Mean: 7777.20 , Min: 3202.55 , Max: 15384.36 , Median: 7339.99, Dealed/Records: 81920/255516,, Time: 2019.05.07 10:45:32\n",
      "epoch: 14 , Train Loss: 15.801232 , Mean: 7755.95 , Min: 3156.27 , Max: 15539.57 , Median: 7310.25, Dealed/Records: 98304/255516,, Time: 2019.05.07 10:45:39\n",
      "epoch: 14 , Train Loss: 15.477040 , Mean: 7736.07 , Min: 3211.29 , Max: 15287.88 , Median: 7311.36, Dealed/Records: 114688/255516,, Time: 2019.05.07 10:45:46\n",
      "epoch: 14 , Train Loss: 16.079067 , Mean: 7757.63 , Min: 3176.54 , Max: 15315.20 , Median: 7317.86, Dealed/Records: 131072/255516,, Time: 2019.05.07 10:45:53\n",
      "epoch: 14 , Train Loss: 15.141133 , Mean: 7724.05 , Min: 3251.48 , Max: 15164.57 , Median: 7271.14, Dealed/Records: 147456/255516,, Time: 2019.05.07 10:46:00\n",
      "epoch: 14 , Train Loss: 15.405864 , Mean: 7750.99 , Min: 3163.04 , Max: 15589.47 , Median: 7322.92, Dealed/Records: 163840/255516,, Time: 2019.05.07 10:46:08\n",
      "epoch: 14 , Train Loss: 15.619741 , Mean: 7722.80 , Min: 2974.54 , Max: 15712.72 , Median: 7248.10, Dealed/Records: 180224/255516,, Time: 2019.05.07 10:46:17\n",
      "epoch: 14 , Train Loss: 15.017667 , Mean: 7747.64 , Min: 3003.36 , Max: 15132.33 , Median: 7303.54, Dealed/Records: 196608/255516,, Time: 2019.05.07 10:46:27\n",
      "epoch: 14 , Train Loss: 15.275415 , Mean: 7720.91 , Min: 2897.89 , Max: 15700.08 , Median: 7293.92, Dealed/Records: 212992/255516,, Time: 2019.05.07 10:46:36\n",
      "epoch: 14 , Train Loss: 15.522674 , Mean: 7736.91 , Min: 2929.75 , Max: 15770.32 , Median: 7280.27, Dealed/Records: 229376/255516,, Time: 2019.05.07 10:46:43\n",
      "epoch: 14 , Train Loss: 15.372081 , Mean: 7720.11 , Min: 3045.04 , Max: 15452.16 , Median: 7272.77, Dealed/Records: 245760/255516,, Time: 2019.05.07 10:46:50\n",
      "epoch: 14 , Train Loss: 15.640186 , Mean: 7741.53 , Min: 3126.50 , Max: 15524.09 , Median: 7255.52, Dealed/Records: 262144/255516,, Time: 2019.05.07 10:46:55\n",
      "epoch: 15 , Train Loss: 15.374615 , Mean: 7739.45 , Min: 3077.21 , Max: 15471.49 , Median: 7306.83, Dealed/Records: 16384/255516,, Time: 2019.05.07 10:47:02\n",
      "epoch: 15 , Train Loss: 15.002385 , Mean: 7709.91 , Min: 2904.28 , Max: 15676.32 , Median: 7277.25, Dealed/Records: 32768/255516,, Time: 2019.05.07 10:47:08\n",
      "epoch: 15 , Train Loss: 15.106315 , Mean: 7716.14 , Min: 2848.39 , Max: 15336.22 , Median: 7206.55, Dealed/Records: 49152/255516,, Time: 2019.05.07 10:47:15\n",
      "epoch: 15 , Train Loss: 15.338599 , Mean: 7716.69 , Min: 3041.15 , Max: 15430.05 , Median: 7234.12, Dealed/Records: 65536/255516,, Time: 2019.05.07 10:47:22\n",
      "epoch: 15 , Train Loss: 15.215313 , Mean: 7764.25 , Min: 3067.81 , Max: 15663.62 , Median: 7302.29, Dealed/Records: 81920/255516,, Time: 2019.05.07 10:47:29\n",
      "epoch: 15 , Train Loss: 15.427335 , Mean: 7742.05 , Min: 3069.94 , Max: 15778.04 , Median: 7268.14, Dealed/Records: 98304/255516,, Time: 2019.05.07 10:47:36\n",
      "epoch: 15 , Train Loss: 15.113831 , Mean: 7720.64 , Min: 3078.65 , Max: 15624.07 , Median: 7263.75, Dealed/Records: 114688/255516,, Time: 2019.05.07 10:47:43\n",
      "epoch: 15 , Train Loss: 15.711610 , Mean: 7743.25 , Min: 3105.20 , Max: 15470.98 , Median: 7272.69, Dealed/Records: 131072/255516,, Time: 2019.05.07 10:47:50\n",
      "epoch: 15 , Train Loss: 14.788400 , Mean: 7708.15 , Min: 3105.16 , Max: 15356.11 , Median: 7234.48, Dealed/Records: 147456/255516,, Time: 2019.05.07 10:47:57\n",
      "epoch: 15 , Train Loss: 15.065198 , Mean: 7735.91 , Min: 3029.16 , Max: 15813.51 , Median: 7274.93, Dealed/Records: 163840/255516,, Time: 2019.05.07 10:48:04\n",
      "epoch: 15 , Train Loss: 15.267728 , Mean: 7707.55 , Min: 2865.99 , Max: 15975.88 , Median: 7209.30, Dealed/Records: 180224/255516,, Time: 2019.05.07 10:48:11\n",
      "epoch: 15 , Train Loss: 14.676945 , Mean: 7733.08 , Min: 2788.65 , Max: 15325.05 , Median: 7253.17, Dealed/Records: 196608/255516,, Time: 2019.05.07 10:48:18\n",
      "epoch: 15 , Train Loss: 14.944440 , Mean: 7705.97 , Min: 2843.20 , Max: 15937.07 , Median: 7244.11, Dealed/Records: 212992/255516,, Time: 2019.05.07 10:48:24\n",
      "epoch: 15 , Train Loss: 15.191093 , Mean: 7722.43 , Min: 2842.20 , Max: 16043.16 , Median: 7242.50, Dealed/Records: 229376/255516,, Time: 2019.05.07 10:48:31\n",
      "epoch: 15 , Train Loss: 15.052448 , Mean: 7704.40 , Min: 2857.52 , Max: 15709.50 , Median: 7228.11, Dealed/Records: 245760/255516,, Time: 2019.05.07 10:48:38\n",
      "epoch: 15 , Train Loss: 15.316126 , Mean: 7727.14 , Min: 3035.96 , Max: 15753.39 , Median: 7219.70, Dealed/Records: 262144/255516,, Time: 2019.05.07 10:48:43\n",
      "epoch: 16 , Train Loss: 15.064850 , Mean: 7725.26 , Min: 3011.90 , Max: 15576.99 , Median: 7265.87, Dealed/Records: 16384/255516,, Time: 2019.05.07 10:48:50\n",
      "epoch: 16 , Train Loss: 14.711425 , Mean: 7692.95 , Min: 2839.42 , Max: 15848.95 , Median: 7233.11, Dealed/Records: 32768/255516,, Time: 2019.05.07 10:48:56\n",
      "epoch: 16 , Train Loss: 14.805015 , Mean: 7700.19 , Min: 2814.74 , Max: 15513.28 , Median: 7168.85, Dealed/Records: 49152/255516,, Time: 2019.05.07 10:49:04\n",
      "epoch: 16 , Train Loss: 15.045799 , Mean: 7700.28 , Min: 2954.73 , Max: 15678.58 , Median: 7194.16, Dealed/Records: 65536/255516,, Time: 2019.05.07 10:49:11\n",
      "epoch: 16 , Train Loss: 14.930012 , Mean: 7750.69 , Min: 2975.30 , Max: 15876.69 , Median: 7273.58, Dealed/Records: 81920/255516,, Time: 2019.05.07 10:49:18\n",
      "epoch: 16 , Train Loss: 15.146566 , Mean: 7727.83 , Min: 2962.13 , Max: 15966.50 , Median: 7232.91, Dealed/Records: 98304/255516,, Time: 2019.05.07 10:49:24\n",
      "epoch: 16 , Train Loss: 14.841359 , Mean: 7705.12 , Min: 2977.03 , Max: 15884.96 , Median: 7234.01, Dealed/Records: 114688/255516,, Time: 2019.05.07 10:49:31\n",
      "epoch: 16 , Train Loss: 15.436727 , Mean: 7728.62 , Min: 3011.75 , Max: 15572.80 , Median: 7248.56, Dealed/Records: 131072/255516,, Time: 2019.05.07 10:49:38\n",
      "epoch: 16 , Train Loss: 14.525759 , Mean: 7692.36 , Min: 2900.26 , Max: 15535.67 , Median: 7196.44, Dealed/Records: 147456/255516,, Time: 2019.05.07 10:49:45\n"
     ]
    },
    {
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     "output_type": "stream",
     "text": [
      "epoch: 16 , Train Loss: 14.811927 , Mean: 7721.21 , Min: 2940.20 , Max: 15992.45 , Median: 7240.82, Dealed/Records: 163840/255516,, Time: 2019.05.07 10:49:52\n",
      "epoch: 16 , Train Loss: 15.002791 , Mean: 7692.94 , Min: 2781.59 , Max: 16174.67 , Median: 7176.82, Dealed/Records: 180224/255516,, Time: 2019.05.07 10:49:59\n",
      "epoch: 16 , Train Loss: 14.425518 , Mean: 7719.28 , Min: 2631.38 , Max: 15537.34 , Median: 7225.31, Dealed/Records: 196608/255516,, Time: 2019.05.07 10:50:05\n",
      "epoch: 16 , Train Loss: 14.700111 , Mean: 7691.87 , Min: 2824.74 , Max: 16110.73 , Median: 7213.94, Dealed/Records: 212992/255516,, Time: 2019.05.07 10:50:12\n",
      "epoch: 16 , Train Loss: 14.945088 , Mean: 7708.89 , Min: 2780.52 , Max: 16256.01 , Median: 7203.83, Dealed/Records: 229376/255516,, Time: 2019.05.07 10:50:19\n",
      "epoch: 16 , Train Loss: 14.815495 , Mean: 7690.14 , Min: 2711.38 , Max: 15913.34 , Median: 7192.65, Dealed/Records: 245760/255516,, Time: 2019.05.07 10:50:26\n",
      "epoch: 16 , Train Loss: 15.077161 , Mean: 7714.00 , Min: 2941.34 , Max: 15932.18 , Median: 7183.64, Dealed/Records: 262144/255516,, Time: 2019.05.07 10:50:30\n",
      "epoch: 17 , Train Loss: 14.835876 , Mean: 7712.59 , Min: 2950.00 , Max: 15750.18 , Median: 7230.35, Dealed/Records: 16384/255516,, Time: 2019.05.07 10:50:37\n",
      "epoch: 17 , Train Loss: 14.498151 , Mean: 7678.05 , Min: 2799.85 , Max: 15982.05 , Median: 7201.45, Dealed/Records: 32768/255516,, Time: 2019.05.07 10:50:44\n",
      "epoch: 17 , Train Loss: 14.582202 , Mean: 7686.33 , Min: 2811.35 , Max: 15636.62 , Median: 7132.65, Dealed/Records: 49152/255516,, Time: 2019.05.07 10:50:51\n",
      "epoch: 17 , Train Loss: 14.829600 , Mean: 7686.24 , Min: 2820.15 , Max: 15883.08 , Median: 7149.52, Dealed/Records: 65536/255516,, Time: 2019.05.07 10:50:58\n",
      "epoch: 17 , Train Loss: 14.719381 , Mean: 7739.04 , Min: 2918.58 , Max: 16045.76 , Median: 7249.77, Dealed/Records: 81920/255516,, Time: 2019.05.07 10:51:05\n",
      "epoch: 17 , Train Loss: 14.939319 , Mean: 7715.79 , Min: 2902.88 , Max: 16125.69 , Median: 7210.32, Dealed/Records: 98304/255516,, Time: 2019.05.07 10:51:12\n",
      "epoch: 17 , Train Loss: 14.640912 , Mean: 7692.13 , Min: 2910.80 , Max: 16092.10 , Median: 7214.90, Dealed/Records: 114688/255516,, Time: 2019.05.07 10:51:19\n",
      "epoch: 17 , Train Loss: 15.234701 , Mean: 7716.27 , Min: 2954.10 , Max: 15643.05 , Median: 7216.34, Dealed/Records: 131072/255516,, Time: 2019.05.07 10:51:26\n",
      "epoch: 17 , Train Loss: 14.333842 , Mean: 7679.16 , Min: 2729.76 , Max: 15752.07 , Median: 7161.57, Dealed/Records: 147456/255516,, Time: 2019.05.07 10:51:33\n",
      "epoch: 17 , Train Loss: 14.627251 , Mean: 7709.05 , Min: 2875.44 , Max: 16146.18 , Median: 7208.39, Dealed/Records: 163840/255516,, Time: 2019.05.07 10:51:39\n",
      "epoch: 17 , Train Loss: 14.806613 , Mean: 7681.03 , Min: 2718.72 , Max: 16331.63 , Median: 7148.51, Dealed/Records: 180224/255516,, Time: 2019.05.07 10:51:46\n",
      "epoch: 17 , Train Loss: 14.243527 , Mean: 7708.03 , Min: 2519.80 , Max: 15751.64 , Median: 7202.62, Dealed/Records: 196608/255516,, Time: 2019.05.07 10:51:53\n",
      "epoch: 17 , Train Loss: 14.523754 , Mean: 7680.29 , Min: 2832.43 , Max: 16242.77 , Median: 7181.41, Dealed/Records: 212992/255516,, Time: 2019.05.07 10:52:00\n",
      "epoch: 17 , Train Loss: 14.765503 , Mean: 7697.69 , Min: 2738.72 , Max: 16427.60 , Median: 7174.16, Dealed/Records: 229376/255516,, Time: 2019.05.07 10:52:07\n",
      "epoch: 17 , Train Loss: 14.642892 , Mean: 7678.39 , Min: 2604.06 , Max: 16080.60 , Median: 7172.12, Dealed/Records: 245760/255516,, Time: 2019.05.07 10:52:14\n",
      "epoch: 17 , Train Loss: 14.904054 , Mean: 7703.01 , Min: 2894.69 , Max: 16077.94 , Median: 7153.84, Dealed/Records: 262144/255516,, Time: 2019.05.07 10:52:18\n",
      "epoch: 18 , Train Loss: 14.669748 , Mean: 7702.07 , Min: 2898.20 , Max: 15918.27 , Median: 7206.86, Dealed/Records: 16384/255516,, Time: 2019.05.07 10:52:25\n",
      "epoch: 18 , Train Loss: 14.345059 , Mean: 7665.60 , Min: 2777.65 , Max: 16089.58 , Median: 7173.88, Dealed/Records: 32768/255516,, Time: 2019.05.07 10:52:32\n",
      "epoch: 18 , Train Loss: 14.420349 , Mean: 7674.66 , Min: 2828.22 , Max: 15745.48 , Median: 7107.74, Dealed/Records: 49152/255516,, Time: 2019.05.07 10:52:39\n",
      "epoch: 18 , Train Loss: 14.672772 , Mean: 7674.48 , Min: 2672.94 , Max: 16046.88 , Median: 7122.63, Dealed/Records: 65536/255516,, Time: 2019.05.07 10:52:45\n",
      "epoch: 18 , Train Loss: 14.566418 , Mean: 7729.09 , Min: 2888.76 , Max: 16184.40 , Median: 7230.97, Dealed/Records: 81920/255516,, Time: 2019.05.07 10:52:52\n",
      "epoch: 18 , Train Loss: 14.788890 , Mean: 7705.53 , Min: 2886.73 , Max: 16265.16 , Median: 7184.38, Dealed/Records: 98304/255516,, Time: 2019.05.07 10:52:59\n",
      "epoch: 18 , Train Loss: 14.495813 , Mean: 7681.05 , Min: 2870.26 , Max: 16258.09 , Median: 7196.07, Dealed/Records: 114688/255516,, Time: 2019.05.07 10:53:06\n",
      "epoch: 18 , Train Loss: 15.088815 , Mean: 7705.59 , Min: 2924.13 , Max: 15692.58 , Median: 7201.43, Dealed/Records: 131072/255516,, Time: 2019.05.07 10:53:13\n",
      "epoch: 18 , Train Loss: 14.195911 , Mean: 7667.76 , Min: 2592.34 , Max: 15931.21 , Median: 7140.01, Dealed/Records: 147456/255516,, Time: 2019.05.07 10:53:20\n",
      "epoch: 18 , Train Loss: 14.494990 , Mean: 7698.53 , Min: 2821.64 , Max: 16281.37 , Median: 7191.30, Dealed/Records: 163840/255516,, Time: 2019.05.07 10:53:27\n",
      "epoch: 18 , Train Loss: 14.663385 , Mean: 7670.75 , Min: 2671.59 , Max: 16457.94 , Median: 7110.67, Dealed/Records: 180224/255516,, Time: 2019.05.07 10:53:34\n",
      "epoch: 18 , Train Loss: 14.113897 , Mean: 7698.26 , Min: 2442.36 , Max: 15930.21 , Median: 7182.63, Dealed/Records: 196608/255516,, Time: 2019.05.07 10:53:41\n",
      "epoch: 18 , Train Loss: 14.398943 , Mean: 7670.20 , Min: 2855.76 , Max: 16343.97 , Median: 7150.38, Dealed/Records: 212992/255516,, Time: 2019.05.07 10:53:47\n",
      "epoch: 18 , Train Loss: 14.636266 , Mean: 7687.79 , Min: 2710.64 , Max: 16566.96 , Median: 7153.78, Dealed/Records: 229376/255516,, Time: 2019.05.07 10:53:54\n",
      "epoch: 18 , Train Loss: 14.519077 , Mean: 7668.13 , Min: 2523.32 , Max: 16218.89 , Median: 7144.24, Dealed/Records: 245760/255516,, Time: 2019.05.07 10:54:01\n",
      "epoch: 18 , Train Loss: 14.780800 , Mean: 7693.27 , Min: 2829.38 , Max: 16198.71 , Median: 7139.81, Dealed/Records: 262144/255516,, Time: 2019.05.07 10:54:05\n",
      "epoch: 19 , Train Loss: 14.551181 , Mean: 7692.78 , Min: 2794.57 , Max: 16048.95 , Median: 7193.71, Dealed/Records: 16384/255516,, Time: 2019.05.07 10:54:12\n",
      "epoch: 19 , Train Loss: 14.236857 , Mean: 7654.74 , Min: 2766.26 , Max: 16177.21 , Median: 7157.36, Dealed/Records: 32768/255516,, Time: 2019.05.07 10:54:19\n",
      "epoch: 19 , Train Loss: 14.304570 , Mean: 7664.46 , Min: 2856.57 , Max: 15877.90 , Median: 7074.71, Dealed/Records: 49152/255516,, Time: 2019.05.07 10:54:26\n",
      "epoch: 19 , Train Loss: 14.560574 , Mean: 7664.29 , Min: 2558.54 , Max: 16173.70 , Median: 7085.12, Dealed/Records: 65536/255516,, Time: 2019.05.07 10:54:33\n",
      "epoch: 19 , Train Loss: 14.456708 , Mean: 7720.33 , Min: 2877.84 , Max: 16299.79 , Median: 7224.71, Dealed/Records: 81920/255516,, Time: 2019.05.07 10:54:40\n",
      "epoch: 19 , Train Loss: 14.681130 , Mean: 7696.55 , Min: 2889.39 , Max: 16388.34 , Median: 7161.26, Dealed/Records: 98304/255516,, Time: 2019.05.07 10:54:46\n",
      "epoch: 19 , Train Loss: 14.391928 , Mean: 7671.47 , Min: 2847.54 , Max: 16391.38 , Median: 7173.43, Dealed/Records: 114688/255516,, Time: 2019.05.07 10:54:53\n",
      "epoch: 19 , Train Loss: 14.984678 , Mean: 7696.32 , Min: 2890.74 , Max: 15832.26 , Median: 7192.66, Dealed/Records: 131072/255516,, Time: 2019.05.07 10:55:00\n",
      "epoch: 19 , Train Loss: 14.097856 , Mean: 7657.92 , Min: 2481.45 , Max: 16076.19 , Median: 7099.37, Dealed/Records: 147456/255516,, Time: 2019.05.07 10:55:07\n",
      "epoch: 19 , Train Loss: 14.401429 , Mean: 7689.47 , Min: 2784.02 , Max: 16401.25 , Median: 7178.03, Dealed/Records: 163840/255516,, Time: 2019.05.07 10:55:14\n",
      "epoch: 19 , Train Loss: 14.559795 , Mean: 7662.02 , Min: 2636.33 , Max: 16561.66 , Median: 7079.96, Dealed/Records: 180224/255516,, Time: 2019.05.07 10:55:21\n",
      "epoch: 19 , Train Loss: 14.022507 , Mean: 7689.95 , Min: 2391.34 , Max: 16079.21 , Median: 7162.72, Dealed/Records: 196608/255516,, Time: 2019.05.07 10:55:27\n",
      "epoch: 19 , Train Loss: 14.311777 , Mean: 7661.62 , Min: 2887.23 , Max: 16422.80 , Median: 7136.66, Dealed/Records: 212992/255516,, Time: 2019.05.07 10:55:34\n"
     ]
    },
    {
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     "output_type": "stream",
     "text": [
      "epoch: 19 , Train Loss: 14.544106 , Mean: 7679.38 , Min: 2692.46 , Max: 16681.29 , Median: 7135.93, Dealed/Records: 229376/255516,, Time: 2019.05.07 10:55:42\n",
      "epoch: 19 , Train Loss: 14.430850 , Mean: 7659.45 , Min: 2463.81 , Max: 16334.28 , Median: 7120.01, Dealed/Records: 245760/255516,, Time: 2019.05.07 10:55:49\n",
      "epoch: 19 , Train Loss: 14.693884 , Mean: 7685.03 , Min: 2724.49 , Max: 16300.91 , Median: 7132.98, Dealed/Records: 262144/255516,, Time: 2019.05.07 10:55:54\n",
      "epoch: 20 , Train Loss: 14.467331 , Mean: 7684.95 , Min: 2704.55 , Max: 16148.10 , Median: 7191.15, Dealed/Records: 16384/255516,, Time: 2019.05.07 10:56:01\n",
      "epoch: 20 , Train Loss: 14.161044 , Mean: 7645.66 , Min: 2761.81 , Max: 16249.66 , Median: 7144.32, Dealed/Records: 32768/255516,, Time: 2019.05.07 10:56:08\n",
      "epoch: 20 , Train Loss: 14.222211 , Mean: 7655.90 , Min: 2888.59 , Max: 15984.70 , Median: 7043.61, Dealed/Records: 49152/255516,, Time: 2019.05.07 10:56:15\n",
      "epoch: 20 , Train Loss: 14.480794 , Mean: 7655.85 , Min: 2471.28 , Max: 16269.58 , Median: 7060.14, Dealed/Records: 65536/255516,, Time: 2019.05.07 10:56:25\n",
      "epoch: 20 , Train Loss: 14.378383 , Mean: 7712.99 , Min: 2879.95 , Max: 16397.81 , Median: 7220.01, Dealed/Records: 81920/255516,, Time: 2019.05.07 10:56:34\n",
      "epoch: 20 , Train Loss: 14.604360 , Mean: 7689.10 , Min: 2779.16 , Max: 16497.59 , Median: 7157.36, Dealed/Records: 98304/255516,, Time: 2019.05.07 10:56:43\n",
      "epoch: 20 , Train Loss: 14.317861 , Mean: 7663.56 , Min: 2837.09 , Max: 16498.86 , Median: 7160.89, Dealed/Records: 114688/255516,, Time: 2019.05.07 10:56:50\n",
      "epoch: 20 , Train Loss: 14.910505 , Mean: 7688.61 , Min: 2867.36 , Max: 15957.13 , Median: 7186.49, Dealed/Records: 131072/255516,, Time: 2019.05.07 10:56:57\n",
      "epoch: 20 , Train Loss: 14.028181 , Mean: 7649.78 , Min: 2394.22 , Max: 16191.75 , Median: 7066.61, Dealed/Records: 147456/255516,, Time: 2019.05.07 10:57:04\n",
      "epoch: 20 , Train Loss: 14.335475 , Mean: 7681.96 , Min: 2758.76 , Max: 16507.33 , Median: 7166.19, Dealed/Records: 163840/255516,, Time: 2019.05.07 10:57:11\n",
      "epoch: 20 , Train Loss: 14.484860 , Mean: 7654.85 , Min: 2610.31 , Max: 16647.89 , Median: 7053.19, Dealed/Records: 180224/255516,, Time: 2019.05.07 10:57:18\n",
      "epoch: 20 , Train Loss: 13.957952 , Mean: 7683.10 , Min: 2360.32 , Max: 16202.89 , Median: 7142.63, Dealed/Records: 196608/255516,, Time: 2019.05.07 10:57:25\n",
      "epoch: 20 , Train Loss: 14.250952 , Mean: 7654.49 , Min: 2884.09 , Max: 16484.66 , Median: 7112.33, Dealed/Records: 212992/255516,, Time: 2019.05.07 10:57:32\n",
      "epoch: 20 , Train Loss: 14.478098 , Mean: 7672.40 , Min: 2605.65 , Max: 16775.08 , Median: 7120.35, Dealed/Records: 229376/255516,, Time: 2019.05.07 10:57:38\n",
      "epoch: 20 , Train Loss: 14.367763 , Mean: 7652.24 , Min: 2421.22 , Max: 16430.57 , Median: 7097.05, Dealed/Records: 245760/255516,, Time: 2019.05.07 10:57:45\n",
      "epoch: 20 , Train Loss: 14.632458 , Mean: 7678.18 , Min: 2647.72 , Max: 16387.77 , Median: 7120.80, Dealed/Records: 262144/255516,, Time: 2019.05.07 10:57:49\n",
      "epoch: 21 , Train Loss: 14.407872 , Mean: 7678.46 , Min: 2636.83 , Max: 16221.00 , Median: 7192.11, Dealed/Records: 16384/255516,, Time: 2019.05.07 10:57:56\n",
      "epoch: 21 , Train Loss: 14.107655 , Mean: 7638.20 , Min: 2740.43 , Max: 16308.59 , Median: 7130.96, Dealed/Records: 32768/255516,, Time: 2019.05.07 10:58:03\n",
      "epoch: 21 , Train Loss: 14.163263 , Mean: 7648.84 , Min: 2793.21 , Max: 16069.98 , Median: 7003.47, Dealed/Records: 49152/255516,, Time: 2019.05.07 10:58:10\n",
      "epoch: 21 , Train Loss: 14.423592 , Mean: 7648.93 , Min: 2405.39 , Max: 16339.85 , Median: 7039.03, Dealed/Records: 65536/255516,, Time: 2019.05.07 10:58:17\n",
      "epoch: 21 , Train Loss: 14.322046 , Mean: 7706.93 , Min: 2841.87 , Max: 16480.71 , Median: 7219.56, Dealed/Records: 81920/255516,, Time: 2019.05.07 10:58:24\n",
      "epoch: 21 , Train Loss: 14.549122 , Mean: 7682.95 , Min: 2689.48 , Max: 16592.73 , Median: 7144.50, Dealed/Records: 98304/255516,, Time: 2019.05.07 10:58:31\n",
      "epoch: 21 , Train Loss: 14.264333 , Mean: 7657.08 , Min: 2805.62 , Max: 16584.61 , Median: 7150.74, Dealed/Records: 114688/255516,, Time: 2019.05.07 10:58:38\n",
      "epoch: 21 , Train Loss: 14.857069 , Mean: 7682.30 , Min: 2809.68 , Max: 16058.51 , Median: 7184.68, Dealed/Records: 131072/255516,, Time: 2019.05.07 10:58:45\n",
      "epoch: 21 , Train Loss: 13.977918 , Mean: 7643.13 , Min: 2330.32 , Max: 16282.75 , Median: 7028.04, Dealed/Records: 147456/255516,, Time: 2019.05.07 10:58:52\n",
      "epoch: 21 , Train Loss: 14.288307 , Mean: 7675.79 , Min: 2742.74 , Max: 16599.38 , Median: 7151.07, Dealed/Records: 163840/255516,, Time: 2019.05.07 10:58:58\n",
      "epoch: 21 , Train Loss: 14.429865 , Mean: 7649.04 , Min: 2591.63 , Max: 16719.10 , Median: 7020.46, Dealed/Records: 180224/255516,, Time: 2019.05.07 10:59:05\n",
      "epoch: 21 , Train Loss: 13.911458 , Mean: 7677.53 , Min: 2343.95 , Max: 16304.11 , Median: 7134.35, Dealed/Records: 196608/255516,, Time: 2019.05.07 10:59:12\n",
      "epoch: 21 , Train Loss: 14.207836 , Mean: 7648.70 , Min: 2836.52 , Max: 16532.64 , Median: 7086.49, Dealed/Records: 212992/255516,, Time: 2019.05.07 10:59:19\n",
      "epoch: 21 , Train Loss: 14.429853 , Mean: 7666.70 , Min: 2523.27 , Max: 16851.14 , Median: 7091.78, Dealed/Records: 229376/255516,, Time: 2019.05.07 10:59:26\n",
      "epoch: 21 , Train Loss: 14.321724 , Mean: 7646.37 , Min: 2381.29 , Max: 16509.80 , Median: 7065.02, Dealed/Records: 245760/255516,, Time: 2019.05.07 10:59:33\n",
      "epoch: 21 , Train Loss: 14.588154 , Mean: 7672.58 , Min: 2594.03 , Max: 16460.88 , Median: 7117.03, Dealed/Records: 262144/255516,, Time: 2019.05.07 10:59:37\n",
      "epoch: 22 , Train Loss: 14.364850 , Mean: 7673.19 , Min: 2587.52 , Max: 16273.00 , Median: 7181.03, Dealed/Records: 16384/255516,, Time: 2019.05.07 10:59:44\n",
      "epoch: 22 , Train Loss: 14.068986 , Mean: 7632.15 , Min: 2714.80 , Max: 16355.55 , Median: 7117.57, Dealed/Records: 32768/255516,, Time: 2019.05.07 10:59:51\n",
      "epoch: 22 , Train Loss: 14.119973 , Mean: 7643.10 , Min: 2718.96 , Max: 16137.65 , Median: 6975.10, Dealed/Records: 49152/255516,, Time: 2019.05.07 10:59:58\n",
      "epoch: 22 , Train Loss: 14.381575 , Mean: 7643.39 , Min: 2357.33 , Max: 16389.79 , Median: 7002.71, Dealed/Records: 65536/255516,, Time: 2019.05.07 11:00:05\n",
      "epoch: 22 , Train Loss: 14.280423 , Mean: 7702.03 , Min: 2802.22 , Max: 16550.05 , Median: 7204.86, Dealed/Records: 81920/255516,, Time: 2019.05.07 11:00:11\n",
      "epoch: 22 , Train Loss: 14.508299 , Mean: 7677.97 , Min: 2622.60 , Max: 16673.88 , Median: 7128.41, Dealed/Records: 98304/255516,, Time: 2019.05.07 11:00:18\n",
      "epoch: 22 , Train Loss: 14.224408 , Mean: 7651.88 , Min: 2753.27 , Max: 16652.14 , Median: 7149.81, Dealed/Records: 114688/255516,, Time: 2019.05.07 11:00:25\n",
      "epoch: 22 , Train Loss: 14.817321 , Mean: 7677.24 , Min: 2769.23 , Max: 16140.40 , Median: 7188.79, Dealed/Records: 131072/255516,, Time: 2019.05.07 11:00:32\n",
      "epoch: 22 , Train Loss: 13.940443 , Mean: 7637.84 , Min: 2283.28 , Max: 16353.77 , Median: 6995.79, Dealed/Records: 147456/255516,, Time: 2019.05.07 11:00:39\n",
      "epoch: 22 , Train Loss: 14.253363 , Mean: 7670.85 , Min: 2733.50 , Max: 16677.67 , Median: 7143.76, Dealed/Records: 163840/255516,, Time: 2019.05.07 11:00:46\n",
      "epoch: 22 , Train Loss: 14.388285 , Mean: 7644.46 , Min: 2579.61 , Max: 16777.81 , Median: 6989.50, Dealed/Records: 180224/255516,, Time: 2019.05.07 11:00:53\n",
      "epoch: 22 , Train Loss: 13.876657 , Mean: 7673.12 , Min: 2338.02 , Max: 16385.83 , Median: 7118.83, Dealed/Records: 196608/255516,, Time: 2019.05.07 11:01:00\n",
      "epoch: 22 , Train Loss: 14.176060 , Mean: 7644.13 , Min: 2796.88 , Max: 16569.53 , Median: 7070.82, Dealed/Records: 212992/255516,, Time: 2019.05.07 11:01:07\n",
      "epoch: 22 , Train Loss: 14.393298 , Mean: 7662.18 , Min: 2457.17 , Max: 16912.20 , Median: 7082.35, Dealed/Records: 229376/255516,, Time: 2019.05.07 11:01:14\n",
      "epoch: 22 , Train Loss: 14.286774 , Mean: 7641.71 , Min: 2314.66 , Max: 16574.01 , Median: 7042.15, Dealed/Records: 245760/255516,, Time: 2019.05.07 11:01:21\n",
      "epoch: 22 , Train Loss: 14.554815 , Mean: 7668.16 , Min: 2557.11 , Max: 16521.99 , Median: 7100.71, Dealed/Records: 262144/255516,, Time: 2019.05.07 11:01:26\n",
      "epoch: 23 , Train Loss: 14.332377 , Mean: 7669.05 , Min: 2553.49 , Max: 16309.24 , Median: 7169.52, Dealed/Records: 16384/255516,, Time: 2019.05.07 11:01:33\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "epoch: 23 , Train Loss: 14.039610 , Mean: 7627.40 , Min: 2697.88 , Max: 16392.67 , Median: 7103.38, Dealed/Records: 32768/255516,, Time: 2019.05.07 11:01:39\n",
      "epoch: 23 , Train Loss: 14.086758 , Mean: 7638.61 , Min: 2661.25 , Max: 16191.65 , Median: 6955.12, Dealed/Records: 49152/255516,, Time: 2019.05.07 11:01:46\n",
      "epoch: 23 , Train Loss: 14.349216 , Mean: 7639.08 , Min: 2323.77 , Max: 16424.69 , Median: 6982.91, Dealed/Records: 65536/255516,, Time: 2019.05.07 11:01:53\n",
      "epoch: 23 , Train Loss: 14.248260 , Mean: 7698.20 , Min: 2770.62 , Max: 16608.06 , Median: 7190.03, Dealed/Records: 81920/255516,, Time: 2019.05.07 11:02:00\n",
      "epoch: 23 , Train Loss: 14.476674 , Mean: 7674.07 , Min: 2574.32 , Max: 16742.29 , Median: 7114.50, Dealed/Records: 98304/255516,, Time: 2019.05.07 11:02:08\n",
      "epoch: 23 , Train Loss: 14.193161 , Mean: 7647.82 , Min: 2719.97 , Max: 16705.52 , Median: 7141.40, Dealed/Records: 114688/255516,, Time: 2019.05.07 11:02:14\n",
      "epoch: 23 , Train Loss: 14.786205 , Mean: 7673.30 , Min: 2743.57 , Max: 16206.92 , Median: 7183.25, Dealed/Records: 131072/255516,, Time: 2019.05.07 11:02:21\n",
      "epoch: 23 , Train Loss: 13.910931 , Mean: 7633.73 , Min: 2250.01 , Max: 16409.56 , Median: 6980.15, Dealed/Records: 147456/255516,, Time: 2019.05.07 11:02:28\n",
      "epoch: 23 , Train Loss: 14.225914 , Mean: 7666.95 , Min: 2730.04 , Max: 16743.55 , Median: 7127.13, Dealed/Records: 163840/255516,, Time: 2019.05.07 11:02:35\n",
      "epoch: 23 , Train Loss: 14.355326 , Mean: 7640.90 , Min: 2554.02 , Max: 16826.49 , Median: 6974.48, Dealed/Records: 180224/255516,, Time: 2019.05.07 11:02:42\n",
      "epoch: 23 , Train Loss: 13.849028 , Mean: 7669.67 , Min: 2339.25 , Max: 16451.55 , Median: 7115.70, Dealed/Records: 196608/255516,, Time: 2019.05.07 11:02:48\n",
      "epoch: 23 , Train Loss: 14.151067 , Mean: 7640.52 , Min: 2764.52 , Max: 16598.06 , Median: 7073.11, Dealed/Records: 212992/255516,, Time: 2019.05.07 11:02:55\n",
      "epoch: 23 , Train Loss: 14.364021 , Mean: 7658.59 , Min: 2405.23 , Max: 16961.18 , Median: 7058.71, Dealed/Records: 229376/255516,, Time: 2019.05.07 11:03:02\n",
      "epoch: 23 , Train Loss: 14.258673 , Mean: 7637.99 , Min: 2263.41 , Max: 16625.79 , Median: 7029.74, Dealed/Records: 245760/255516,, Time: 2019.05.07 11:03:09\n",
      "epoch: 23 , Train Loss: 14.528062 , Mean: 7664.61 , Min: 2533.14 , Max: 16572.81 , Median: 7073.50, Dealed/Records: 262144/255516,, Time: 2019.05.07 11:03:13\n",
      "epoch: 24 , Train Loss: 14.306226 , Mean: 7665.71 , Min: 2529.86 , Max: 16333.69 , Median: 7158.53, Dealed/Records: 16384/255516,, Time: 2019.05.07 11:03:20\n",
      "epoch: 24 , Train Loss: 14.015665 , Mean: 7623.58 , Min: 2687.44 , Max: 16421.46 , Median: 7091.19, Dealed/Records: 32768/255516,, Time: 2019.05.07 11:03:27\n",
      "epoch: 24 , Train Loss: 14.059600 , Mean: 7634.96 , Min: 2617.75 , Max: 16234.90 , Median: 6941.46, Dealed/Records: 49152/255516,, Time: 2019.05.07 11:03:34\n",
      "epoch: 24 , Train Loss: 14.322649 , Mean: 7635.63 , Min: 2301.79 , Max: 16448.08 , Median: 6968.67, Dealed/Records: 65536/255516,, Time: 2019.05.07 11:03:40\n",
      "epoch: 24 , Train Loss: 14.221841 , Mean: 7695.11 , Min: 2746.61 , Max: 16655.76 , Median: 7189.79, Dealed/Records: 81920/255516,, Time: 2019.05.07 11:03:47\n",
      "epoch: 24 , Train Loss: 14.450573 , Mean: 7670.90 , Min: 2539.83 , Max: 16798.60 , Median: 7107.04, Dealed/Records: 98304/255516,, Time: 2019.05.07 11:03:54\n",
      "epoch: 24 , Train Loss: 14.167047 , Mean: 7644.54 , Min: 2700.82 , Max: 16747.04 , Median: 7120.07, Dealed/Records: 114688/255516,, Time: 2019.05.07 11:04:01\n",
      "epoch: 24 , Train Loss: 14.760170 , Mean: 7670.14 , Min: 2728.89 , Max: 16260.58 , Median: 7163.79, Dealed/Records: 131072/255516,, Time: 2019.05.07 11:04:08\n",
      "epoch: 24 , Train Loss: 13.886025 , Mean: 7630.46 , Min: 2228.07 , Max: 16453.49 , Median: 6966.43, Dealed/Records: 147456/255516,, Time: 2019.05.07 11:04:14\n",
      "epoch: 24 , Train Loss: 14.202664 , Mean: 7663.80 , Min: 2728.76 , Max: 16797.85 , Median: 7116.43, Dealed/Records: 163840/255516,, Time: 2019.05.07 11:04:21\n",
      "epoch: 24 , Train Loss: 14.327622 , Mean: 7638.09 , Min: 2490.74 , Max: 16866.23 , Median: 6963.12, Dealed/Records: 180224/255516,, Time: 2019.05.07 11:04:28\n",
      "epoch: 24 , Train Loss: 13.825361 , Mean: 7666.92 , Min: 2345.39 , Max: 16503.59 , Median: 7093.55, Dealed/Records: 196608/255516,, Time: 2019.05.07 11:04:35\n",
      "epoch: 24 , Train Loss: 14.129657 , Mean: 7637.67 , Min: 2738.76 , Max: 16620.04 , Median: 7053.07, Dealed/Records: 212992/255516,, Time: 2019.05.07 11:04:41\n",
      "epoch: 24 , Train Loss: 14.338914 , Mean: 7655.75 , Min: 2365.62 , Max: 17000.26 , Median: 7047.46, Dealed/Records: 229376/255516,, Time: 2019.05.07 11:04:48\n",
      "epoch: 24 , Train Loss: 14.234413 , Mean: 7635.04 , Min: 2225.27 , Max: 16667.24 , Median: 7008.04, Dealed/Records: 245760/255516,, Time: 2019.05.07 11:04:55\n",
      "epoch: 24 , Train Loss: 14.504813 , Mean: 7661.81 , Min: 2519.01 , Max: 16614.85 , Median: 7048.65, Dealed/Records: 262144/255516,, Time: 2019.05.07 11:04:59\n"
     ]
    }
   ],
   "source": [
    "from torch.utils.data import DataLoader\n",
    "import torch.nn as nn\n",
    "from torch.nn import init\n",
    "import numpy as np\n",
    "import math\n",
    "import time\n",
    "class SalaryNet(torch.nn.Module):\n",
    "    def __init__(self,in_size,h1_size,h2_size,out_size):\n",
    "        super(SalaryNet,self).__init__()\n",
    "        self.h1 = torch.nn.Linear(in_size,h1_size)\n",
    "        self.relu = torch.nn.ReLU()\n",
    "        self.h2 = torch.nn.Linear(h1_size,h2_size)\n",
    "        self.out = torch.nn.Linear(h2_size,out_size)\n",
    "    def forward(self,x):\n",
    "        h1_relu = self.relu(self.h1(x))\n",
    "        h2_relu = self.relu(self.h2(h1_relu))\n",
    "        predict = self.out(h2_relu)\n",
    "        return predict  \n",
    "#训练模型：\n",
    "if __name__ == '__main__':\n",
    "    #定义批大小（每次传递64条记录给模型训练，充分利用矩阵计算的并行性能）\n",
    "    batch_size = 16384\n",
    "    #定义训练epoch\n",
    "    epoch = 25\n",
    "    # 定义模型\n",
    "    model = SalaryNet(327,100,20,1).to(\"cuda\")\n",
    "    # 初始化权重参数\n",
    "    for layer in model.modules():\n",
    "        if isinstance(layer, nn.Linear):\n",
    "            init.xavier_uniform_(layer.weight)\n",
    "    # 定义优化器\n",
    "    optimizer = torch.optim.Adam(model.parameters(), 0.001)\n",
    "    # 损失函数\n",
    "    criterion = nn.MSELoss()\n",
    "    #定义损失数组，用于可视化训练过程\n",
    "    loss_holder = []\n",
    "    #损失值设置为无限大，每次迭代若损失值比loss_value小则保存模型，并将最新的损失值赋值给loss_value\n",
    "    loss_value = np.inf\n",
    "    step = 0 \n",
    "    for i in range(epoch):\n",
    "        train_count = 0\n",
    "        batchs = 0\n",
    "        for j in DataLoader(dataset, batch_size=batch_size, shuffle=False):\n",
    "            batchs = batchs+1\n",
    "            train_x_data = j[0].float().to(\"cuda\")\n",
    "            train_y_data = j[1].float().to(\"cuda\")\n",
    "            #输出值\n",
    "            out = model(train_x_data)\n",
    "            #损失值\n",
    "            loss = criterion(out.squeeze(1),train_y_data)\n",
    "            #反向传播,先将梯度设置为0，否则该步的梯度会和前面已经计算的梯度累乘\n",
    "            optimizer.zero_grad()\n",
    "            loss.backward()\n",
    "            #更新参数\n",
    "            optimizer.step()\n",
    "            #记录误差\n",
    "            print('epoch: {} , Train Loss: {:.6f} , Mean: {:.2f} , Min: {:.2f} , Max: {:.2f} , Median: {:.2f}, Dealed/Records: {}/{},, Time: {}'. \\\n",
    "                    format(i, math.sqrt(loss / batch_size), out.mean(),\n",
    "                           out.min(), out.max(), out.median(),batchs * batch_size, dataset.__len__(),\n",
    "                           time.strftime('%Y.%m.%d %H:%M:%S', time.localtime(time.time()))))\n",
    "            step+=1\n",
    "            loss_holder.append([step,math.sqrt(loss / batch_size)])\n",
    "            #模型性能有提升则保存模型,并更新loss_value\n",
    "            if loss < loss_value:\n",
    "                torch.save(model, 'model.ckpt')\n",
    "                loss_value = loss"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1440x1080 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "fig = plt.figure(figsize=(20,15))\n",
    "\n",
    "loss_df = pd.DataFrame(loss_holder,columns=[\"time\",\"loss\"])\n",
    "x_times = loss_df[\"time\"].values\n",
    "plt.ylabel(\"Loss\")\n",
    "plt.xlabel(\"times\")\n",
    "plt.plot(loss_df[\"loss\"].values)\n",
    "#plt.xticks([10,100,400,700,1000])\n",
    "#x轴字体倾斜避免重叠\n",
    "fig.autofmt_xdate()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.3"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}
